Subcategories

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• Artificial intelligence & Machine Learning

  Discuss peer review challenges in AI/ML research — submission, review quality, bias, and decision appeals at ICLR, ICML, NeurIPS, AAAI, IJCAI, AISTATS and COLT.

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  lol a few days ago, AAAI just casually dropped the first-round “reviewer gift pack” and it was wild… people opened their dashboard and saw 8 papers at once. hit refresh? suddenly 11. felt like a surprise loot box nobody wanted then on the same day, the system started pulling them back, like “oops, jk.” now it seems to be 3 reviewers per paper… but yeah, still mostly reviewing direct competitors so not exactly a win. and if you only got 1 paper in round one, chances are you’ll be drafted again in round two. mental prep advised the backdrop: 22k+ submissions this year. absolutely bonkers. the random assignment thing made a lot of us worried about another “Who is Adam” moment. the new reciprocal review rules might help a bit, but it still feels messy funny part tho… some folks i know haven’t been assigned a single paper yet, while others are buried alive. truly RNG (Random Number Generator) reviewer roulette at its finest. so yeah, any other reviewers got their “big pack” yanked overnight? would you rather deal with the madness of 8–11 papers, or this slow-burn redistribution? curious how y’all are coping.
• Computer Vision, Graphics & Robotics

  Discuss peer review challenges, submission experiences, decision fairness, reviewer quality, and biases at CVPR, ICCV, ECCV, VR, SIGGRAPH, EUROGRAPHICS, ICRA, IROS, RSS etc.

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  Shocking Cases, Reviewer Rants, Score Dramas, and the True Face of CV Top-tier Peer Review! “Just got a small heart attack reading the title.” — u/Intrepid-Essay-3283, Reddit [image: giphy.gif] Introduction: ICCV 2025 — Not Just Another Year ICCV 2025 might have broken submission records (11,239 papers! 🤯), but what really set this year apart was the open outpouring of review experiences, drama, and critique across communities like Zhihu and Reddit. If you think peer review is just technical feedback, think again. This year, it was a social experiment in bias, randomness, AI-detection accusations, and — sometimes — rare acts of fairness. Below, we dissect dozens of real cases reported by the community. Expect everything: miracle accepts, heartbreak rejections, reviewer bias, AC heroics, AI accusations, desk rejects, and score manipulation. Plus, we bring you the ultimate summary table — all real, all raw. The Hall of Fame: ICCV 2025 Real Review Cases Here’s a complete table of every community case reported above. Each row is a real story. Find your favorite drama! # Initial Score Final Score Rebuttal Effect Decision Reviewer/AC Notes / Notable Points Source/Comment 1 4/4/2 5/4/4 +1, +2 Accept AC sided with authors after strong rebuttal Reddit, ElPelana 2 5/4/4 6/5/4 +1, +1 Reject Meta-review agreed novelty, but blamed single baseline & "misleading" boldface Reddit, Sufficient_Ad_4885 3 5/4/4 5/4/4 None Reject Several strong scores, still rejected Reddit, kjunhot 4 5/5/3 6/5/4 +1, +2 Accept "Should be good" - optimism confirmed! Reddit, Friendly-Angle-5367 5 4/4/4 4/4/4 None Accept "Accept with scores of 4/4/4/4 lol" Reddit, ParticularWork8424 6 5/5/4 6/5/4 +1 Accept No info on spotlight/talk/poster Reddit, Friendly-Angle-5367 7 4/3/2 4/3/3 +1 Accept AC "saved" the paper! Reddit, megaton00 8 5/5/4 6/5/4 +1 Accept (same as #6, poster/talk unknown) Reddit, Virtual_Plum121 9 5/3/2 4/4/2 mixed Reject Rebuttal didn't save it, "incrementality" issue Reddit, realogog 10 5/4/3 - - Accept Community optimism for "5-4-3 is achievable" Reddit, felolorocher 11 4/4/2 4/4/3 +1 Accept AC fought for the paper, luck matters! Reddit, Few_Refrigerator8308 12 4/3/4 4/4/5 +1 Accept Lucky with AC Reddit, Ok-Internet-196 13 5/3/3 4/3/3 -1 (from 5 to 4) Reject Reviewer simply wrote "I read the rebuttals and updated my score." Reddit, chethankodase 14 5/4/1 6/6/1 +1/+2 Reject "The reviewer had a strong personal bias, but the ACs were not convinced" Reddit, ted91512 15 5/3/3 6/5/4 +1/+2 Accept "Accepted, happy ending" Reddit, ridingabuffalo58 16 6/5/4 6/6/4 +1 Accept "Accepted but not sure if poster/oral" Reddit, InstantBuffoonery 17 6/3/2 - None Reject "Strong accept signals" still not enough Reddit, impatiens-capensis 18 5/5/2 5/5/3 +1 Accept "Reject was against the principle of our work" Reddit, SantaSoul 19 6/4/4 6/6/4 +2 Accept Community support for strong scores Reddit, curious_mortal 20 4/4/2 6/4/2 +2 Accept AC considered report about reviewer bias Reddit, DuranRafid 21 3/4/6 3/4/6 None Reject BR reviewer didn't submit final, AC rejected Reddit, Fluff269 22 355 555 +2 Accept "Any chance for oral?" Reddit, Beginning-Youth-6369 23 5/3/2 - - TBD "Had a good rebuttal, let's see!" Reddit, temporal_guy 24 4/3/4 - - TBD "Waiting for good results!" Reddit, Ok-Internet-196 25 5/5/4 5/5/4 None Accept "555 we fn did it boys" Reddit, lifex_ 26 633 554 - Accept "Here we go Hawaii♡" Reddit, DriveOdd5983 27 554 555 +1 Accept "Many thanks to AC" Reddit, GuessAIDoesTheTrick 28 345 545 +2 Accept "My first Accept!" Reddit, Fantastic_Bedroom170 29 4/4/2 232 -2, -2 Reject "Reviewers praised the paper, but still rejected" Reddit, upthread 30 5/4/4 5/4/4 None Reject "Another 5/4/4 reject here!" Reddit, kjunhot 31 432 432 None TBD "432 with hope" Zhihu, 泡泡鱼 32 444 444 None Accept "3 borderline accepts, got in!" Zhihu, 小月 33 553 555 +2 Accept "5-score reviewer roasted the 3-score reviewer" Zhihu, Ealice 34 554 555 +1 Accept "Highlight downgraded to poster, but happy" Zhihu, Frank 35 135 245 +1/+2 Reject "Met a 'bad guy' reviewer" Zhihu, Frank 36 235 445 +2 Accept "Congrats co-authors!" Zhihu, Frank 37 432 432 None Accept "AC appreciated explanation, saved the paper" Zhihu, Feng Qiao 38 442 543 +1/+1 Accept "After all, got in!" Zhihu, 结弦 39 441 441 None TBD "One reviewer 'writing randomly'" Zhihu, ppphhhttt 40 4/4/3/2 - - TBD "Asked to use more datasets for generalization" Zhihu, 随机 41 446 (443) - - TBD "Everyone changed scores last two days" Zhihu, 877129391241 42 553 553 None Accept "Thanks AC for acceptance" Zhihu, Ealice 43 4/4/3/2 - - Accept "First-time submission, fair attack points" Zhihu, 张读白 44 4/4/4 4/4/4 None Accept "Confident, hoping for luck" Zhihu, hellobug 45 5541 - - TBD "Accused of copying concurrent work" Zhihu, 凪·云抹烟霞 46 554 555 +1 Accept "Poster, but AC downgraded highlight" Zhihu, Frank 47 6/3/2 - None Reject High initial, still rejected Reddit, impatiens-capensis 48 432 432 None Accept "Average final 4, some hope" Zhihu, 泡泡鱼 49 563 564 +1 Accept "Grateful to AC!" Zhihu, 夏影 50 6/5/4 6/6/4 +1 Accept "Accepted, not sure if poster or oral" Reddit, InstantBuffoonery NOTE: This is NOT an exhaustive list of all ICCV 2025 papers, but every real individual case reported in the Zhihu and Reddit community discussions included above. Many entries were “update pending” at posting — when the author didn’t share the final result, marked as TBD. Many papers changed hands between accept/reject on details like one reviewer not updating, AC/Meta reviewer overrides, “bad guy”/mean reviewers, and luck with batch cutoff. 🧠 ICCV 2025 Review Insights: What Did We Learn? 1. Luck Matters — Sometimes More Than Merit Multiple papers with 5/5/3 or even 6/5/4 were rejected. Others with one weak reject (2) got in — sometimes only because the AC “fought for it.” "Getting lucky with the reviewers is almost as important as the quality of the paper itself." (Reddit) 2. Reviewer Quality Is All Over the Place Dozens reported short, generic, or careless reviews — sometimes 1-2 lines with major negative impact. Multiple people accused reviewers of being AI-generated (GPT/Claude/etc.) — several ran AI detectors and reported >90% “AI-written.” Desk rejects were sometimes triggered by reviewer irresponsibility (ICCV officially desk-rejected 29 papers for "irresponsible" reviewers). 3. Rebuttal Can Save You… Sometimes Many cases where good rebuttals led to score increases and acceptance. But also numerous stories where reviewers didn’t update, or even lowered scores post-rebuttal without clear reason. 4. Meta-Reviewers & ACs Wield Real Power Several stories where ACs overruled reviewers (for both acceptance and rejection). Meta-reviewer “mistakes” (e.g., recommend accept but click reject) — some authors appealed and got the result changed. 5. System Flaws and Community Frustrations Complaints about the “review lottery”, irresponsible/underqualified reviewers, ACs ignoring rebuttal, and unfixable errors. Many hope for peer review reform: more double-blind accountability, reviewer rating, and even rewards for good reviewing (see this arXiv paper proposing reform). Community Quotes & Highlights "Now I believe in luck, not just science." — Anonymous "Desk reject just before notification, it's a heartbreaker." — 877129391241, Zhihu "I got 555, we did it boys." — lifex, Reddit "Three ACs gave Accept, but it was still rejected — I have no words." — 寄寄子, Zhihu "Training loss increases inference time — is this GPT reviewing?" — Knight, Zhihu "Meta-review: Accept. Final Decision: Reject. Reached out, they fixed it." — fall22_cs_throwaway, Reddit Final Thoughts: Is ICCV Peer Review Broken? ICCV 2025 gave us a microcosm of everything good and bad about large-scale peer review: scientific excellence, reviewer burnout, human bias, reviewer heroism, and plenty of randomness. Takeaways: Prepare your best work, but steel yourself for randomness. Test early on https://review.cspaper.org before and after submission to help build reasonable expectation Craft a strong, detailed rebuttal — sometimes it works miracles. If you sense real injustice, appeal or contact your AC, but don’t count on it. Above all: Don’t take a single decision as a final judgment of your science, your skill, or your future. Join the Conversation! What was YOUR ICCV 2025 review experience? Did you spot AI-generated reviews? Did a miracle rebuttal save your work? Is the peer review crisis fixable, or are we doomed to reviewer roulette forever? “Always hoping for the best! But worse case scenario, one can go for a Workshop with a Proceedings Track!” — Reddit [image: peerreview-nickkim.jpg] Let’s keep pushing for better science — and a better system. If you find this article helpful, insightful, or just painfully relatable, upvote and share with your fellow researchers. The struggle is real, and you are not alone!
• Natural Language Processing

  Discuss peer review, submission experiences, and decision challenges for NLP research at ACL, EMNLP, NAACL, and COLING.

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  The final decisions for EMNLP 2025 have been released, sparking a wave of reactions across research communities on social media such as Zhihu and Reddit. Beyond the excitement of acceptances and the disappointment of rejections, this cycle is marked by a remarkable policy twist: 82 papers were desk-rejected because at least one author had been identified as an irresponsible reviewer. This article provides an in-depth look at the decision process, the broader community responses, and a comprehensive table of decision outcomes shared publicly by researchers. [image: 1755763433631-screenshot-2025-08-21-at-10.02.47.jpg] Key Announcements from the Decision Letter The program chairs’ decision email highlighted several important points: Acceptance Statistics 8174 submissions received. 22.16% accepted to the Main Conference. 17.35% accepted as Findings. 82 papers desk-rejected due to irresponsible reviewer identification. Desk Rejections Linked to Reviewer Misconduct A novel and controversial policy: authors who were flagged as irresponsible reviewers had their own papers automatically desk-rejected. The official blog post elaborates on what qualifies as irresponsible reviewing (e.g., extremely short, low-quality, or AI-generated reviews). Camera-Ready Submissions Deadline: September 19, 2025. Authors must fill in the Responsible NLP checklist, which will be published in the ACL Anthology alongside the paper. Allowed: one extra page for content, one page for limitations (mandatory), optional ethics, unlimited references. Presentation and Logistics Papers must be presented either in person or virtually to be included in proceedings. Oral vs. poster presentation decisions will be finalized after camera-ready submission. Registration deadline: October 3 (at least one author), with early in-person registration by October 6 due to Chinese government approval processes (conference will be in Suzhou). The Desk Rejection Controversy: 82 Papers Removed This year’s 82 desk rejections triggered heated debates. While ensuring reviewer accountability is laudable, punishing co-authors for the actions of a single irresponsible reviewer is unprecedented and raises questions about fairness: Collective punishment? Innocent co-authors had their work invalidated. Transparency gap: The official blog post provided criteria, but the actual identification process is opaque. Potential chilling effect: Researchers may hesitate to serve as reviewers for fear of inadvertently harming their own submissions. The policy signals a stronger stance by ACL conferences toward review quality enforcement, but it also underscores the urgent need for more transparent, community-driven reviewer accountability mechanisms. Community Voices: Decisions Shared by Researchers To capture the breadth of community sentiment, below is a comprehensive table compiling decision outcomes (OA = overall average reviewer scores, Meta = meta-review score) shared publicly across Zhihu, Reddit and X. This table is exhaustive with respect to all shared samples from the provided community discussions. OA Scores (per reviewer) Meta Outcome Track / Notes / User 4, 4, 3 4 Main Meta reviewer wrote a detailed essay, helped acceptance 3.5, 3.5, 2 — Main Initially worried, accepted to main 2.67 (avg) 3.5 Main Shared proudly (“unexpected”) 3.67 4 Main Confirmed traveling to Suzhou 3.33 (4, 3.5, 2.5) 3 Rejected Author frustrated, “don’t understand decision” 3.0 3 Rejected Hoped for Findings, didn’t get in 3.0 3.5 Main (short) Track: multilinguality & language diversity; first-author undergrad 2.33 3.5 Findings Efficient NLP track 3.33 3.5 Main Efficient NLP track 3.5, 3.5, 2.5 2.5 Findings Meta review accused of copy-paste from weakest reviewer 3, 3.5, 4 3 Main Theme track 4, 3, 2 2.5 Rejected One review flagged as AI-generated; rebuttal ignored 4.5, 2.5, 2 — Rejected Meta only two sentences 3.38 3.5 Main Rejected at ACL before; accepted at EMNLP 2, 3, 3 3 Rejected RepresentativeBed838 3.5, 3, 2.5 3.5 Rejected Author shocked 3, 3, 3 3 Rejected Multiple confirmations 5, 4, 3.5 4.5 Main Track: Dialogue and Interactive Systems 3.5, 4.5, 4 4 Main GlitteringEnd5311 3, 3.5, 3.5 3.5 Main Retrieval-Augmented LM track 2.5, 3, 3 3 Findings After rebuttal challenge; author reported meta reviewer 1.5, 3, 3 → rebuttal → 2.5, 3, 3.5 3.5 Main Initially borderline, improved after rebuttal 3.67 3 Main Computational Social Science / NLP for Social Good track 4, 3, 3 3 Main Low-resource track 3.5, 3.5, 3 3.5 Main Low-resource track 4, 3 3 Findings Author sad (“wish it was main”) Overall 3.17 3 Findings JasraTheBland confirmation Overall 3.17 3.5 Main AI Agents track Overall 3.17 3 Findings AI Agents track 4, 3, 2 3.5 Main Responsible-Pie-5882 3.5 (avg) 3.5 Main Few_Refrigerator8308 3, 3, 3.5 → rebuttal → 3.5,3.5,3.5 4.0 Main LLM Efficiency track 3.5, 2.5, 2.5 3 Findings FoxSuspicious7521 3, 3.5, 3.5 3.5 Main ConcernConscious4131 (paper 1) 2, 3, 3.5 3 Rejected ConcernConscious4131 (paper 2) 3, 3, 3 3 Rejected Ok-Dot125 confirmation 3.17 (approx) 3.5 Main Old_Toe_6707 in AI Agents 3.17 (approx) 3 Findings Slight_Armadillo_552 in AI Agents 3, 3, 3 3 Rejected Confirmed again by AdministrativeRub484 4, 3, 2 3.5 Main Responsible-Pie-5882 (duplicate entry but reconfirmed) 3.5, 3.5, 3 3.5 Main breadwineandtits 3, 3, 3 3 Accepted (Findings or Main unclear) NeuralNet7 (saw camera-ready enabled) 2.5 (meta only) 2.5 Findings Mentioned as borderline acceptance 3.0 3.0 Findings shahroz01, expected 4, 3, 2 3.5 Main Responsible-Pie-5882 (explicit post) 3.5, 3.5, 2.5 2.5 Findings Practical_Pomelo_636 3, 3, 3 3 Reject Multiple confirmations across threads 4, 3, 3 3 Findings LastRepair2290 (sad it wasn’t main) 3.5, 3, 2.5 3.5 Rejected Aromatic-Clue-2720 3, 3, 3.5 3.5 Main ConcernConscious4131 2, 3, 3 3 Reject ConcernConscious4131 3, 3, 3 3 Reject Ok-Dot125 again 3.5, 3.5, 3 3.5 Main Few_Refrigerator8308 second report 3.5, 3, 2.5 3.5 Rejected Aromatic-Clue-2720 4, 3, 2 3.5 Main Responsible-Pie-5882 final confirmation 3.5, 3.5, 3 3.5 Main Reconfirmed across threads 3, 3, 3 3 Rejected Reported multiple times 2.5 (OA overall) 3.0 Findings Outrageous-Lake-5569 reference Patterns Emerging From the collected outcomes, some patterns can be observed: Meta ≥ 3.5 often leads to Main acceptance (even when individual OA scores are mediocre, e.g., 2.67). Meta = 3 cases are unstable: some lead to Findings, others to Rejection, and in a few cases even Main. Meta < 3 almost always means rejection, with rare exceptions. Reviewer quality matters: multiple complaints mention meta-reviews simply copy-pasting from the weakest reviewer, undermining rebuttals. This highlights the high variance in borderline cases and explains why so many authors felt frustrated or confused. Conclusion: Lessons from EMNLP 2025 EMNLP 2025 brought both joy and heartbreak. With a Main acceptance rate of just over 22%, competition was fierce. The desk rejections tied to reviewer misconduct added an entirely new layer of controversy that will likely remain debated long after the conference. For researchers, the key takeaways are: Meta review scores dominate: cultivate strong rebuttals and area chair engagement. Borderline cases are unpredictable: even a 3.5 meta may result in Findings instead of Main. Reviewer accountability is a double-edged sword: while improving review quality is necessary, policies that punish co-authors risk alienating the community. As the field grows, the CL community must balance fairness, rigor, and transparency—a challenge as difficult as the NLP problems we study.
• Data Mining & Database

  SIGKDD, SIGMOD, ICDE, CIKM, WSDM, VLDB, ICDM and PODS

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  [image: 1753375505199-866c4b66-8902-4e99-8065-60d1806309a6-vldb2026.png] The International Conference on Very Large Data Bases (VLDB) is a premier annual forum for data management and scalable data science research, bringing together academics, industry engineers, practitioners and users. VLDB 2026 will feature research talks, keynotes, panels, tutorials, demonstrations, industrial sessions and workshops that span the full spectrum of information management topics, from system architecture and theory to large scale experimentation and demanding real world applications. Key areas of interest for its companion journal PVLDB include, but are not limited to, data mining and analytics, data privacy and security, database engines, database performance and manageability, distributed database systems, graph and network data, information integration and data quality, languages, machine learning / AI and databases, novel database architectures, provenance and workflows, specialized and domain-specific data management, text and semi-structured data, and user interfaces. The 52nd International Conference on Very Large Data Bases (VLDB 2026) runs 31 Aug – 4 Sep 2026 in Boston, MA, USA. Peer review is handled via Microsoft’s Conference Management Toolkit (CMT). The submission channel will be PVLDB Vol 19 (rolling research track) with General Chairs Angela Bonifati (Lyon 1 University & IUF, France) and Mirek Riedewald (Northeastern University, USA) Rolling submission calendar (PVLDB Vol 19) Phase Recurring date* Notes Submissions open 20 th of the previous month CMT site opens Paper deadline 1 st of each month (Apr 1 2025 → Mar 1 2026) 17:00 PT hard cut-off Notification / initial reviews 15 th of following month Accept / Major Revision / Reject Revision due ≤ 2.5 months later (1 st of third month) Single-round revision Camera-ready instructions 5 th of the month after acceptance Sent to accepted papers Final cut-off for VLDB 2026 1 Jun 2026 revision deadline Later acceptances roll to VLDB 2027 *See the official CFP for the full calendar. Acceptance statistics (research track) Year Submissions Accepted Rate 2022 976 265 27.15 % 2021 882 212 24 % 2020 827 207 25.03 % 2019 677 128 18.9 % 2013 559 127 22.7 % 2012 659 134 20.3 % 2011 553 100 18.1 % Acceptance has ranged between ~18 % and ~27 % in the PVLDB era. Rolling monthly deadlines have increased submission volume while maintaining selectivity. Emerging research themes (2025 – 2026) Vector databases & retrieval-augmented LMs Hardware / software co-design for LLM workloads Scalable graph management & analytics Multimodal querying & knowledge-rich search with LLMs Submission checklist Use the official PVLDB Vol 19 LaTeX/Word template. Declare all conflicts of interest in CMT. Provide an artifact URL for reproducibility. Submit early (before Jan 2026) to leave revision headroom. Ensure at least one author registers to present in Boston (or via the hybrid option). Key links Main site: https://www.vldb.org/2026/ Research-track CFP & important dates: https://www.vldb.org/2026/call-for-research-track.html PVLDB Vol 19 submission guidelines: https://www.vldb.org/pvldb/volumes/19/submission/ Draft early, align your work with the vector and LLM data system wave, and shine in Boston!
• Software Engineering & System Software

  ICSE, OSDI, SOSP, POPL, PLDI, FSE/ESEC, ISSTA, OOPSLA and ASE

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  It seems CCF is revising the list again: https://www.ccf.org.cn/Academic_Evaluation/By_category/2025-05-09/841985.shtml
• Human Computer Interaction & Visualization

  HCI, CSCW, UniComp, UIST, EuroVis and IEEE VIS

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  [image: 1750758497155-fa715fd6-ed5a-44be-8c8d-84f1645fac47-image.png] CHI remains the flagship venue in the HCI field. It draws researchers from diverse disciplines, consistently puts humans at the center, and amplifies research impact through high quality papers, compelling keynotes, and extensive doctoral consortia. Yet CHI isn’t the entirety of the HCI landscape. It’s just the heart of a much broader ecosystem. Here’s a quick-look field guide Six flagship international HCI conferences Acronym What makes it shine Ideal authors Home page Photo UIST Hardware & novel interface tech; demo heavy culture System / device researchers https://uist.acm.org/2025/ [image: 1750757345992-d6b2b397-f753-40fd-b2b7-2410ed6556b9-image.png] SIGGRAPH Graphics core plus dazzling VR/AR & 3-D interaction showcases Graphics, visual interaction & art-tech hybrids https://www.siggraph.org/ [image: 1750757560460-6657b0b8-06d3-4c27-bc03-6f449a03b7c2-image.png] MobileHCI Interaction in mobile, wearable & ubiquitous contexts Ubicomp oriented, real world applications https://mobilehci.acm.org/2024/ [image: 1750757628685-22f47458-89b5-4f9c-8718-ee89249c1e49-image.png] CSCW Collaboration, remote work & social media at scale Socio-technical & social computing teams https://cscw.acm.org/2025/ [image: 1750757750339-ea17f345-83b9-47f3-af41-6623bdf45eab-image.png] DIS Creative, cultural & critical interaction design UX, speculative & experience driven scholars https://dis.acm.org/2025/ [image: 1750757796645-b1212781-047f-4afc-89a4-e07691e25225-image.png] CHI Broadest scope, human centred ethos, highest brand value Any HCI sub field https://chi2026.acm.org/ [image: 1750757827999-a2b6e621-cbbb-428c-929c-97d243165d19-image.png] Four high-impact HCI journals Journal Focus Good for Home page ACM TOCHI Major theoretical / methodological breakthroughs Large, mature studies needing depth https://dl.acm.org/journal/tochi IJHCS <br>(International Journal of Human-Computer Studies) Cognition → innovation → UX Theory blended with applications https://www.sciencedirect.com/journal/international-journal-of-human-computer-studies CHB <br>(Computers in Human Behavior) Psychological & behavioural angles on HCI Quant-heavy user studies & surveys https://www.sciencedirect.com/journal/computers-in-human-behavior IJHCI <br>(International Journal of Human-Computer Interaction) Cognitive, creative, health-related themes Breadth from conceptual to applied work https://www.tandfonline.com/journals/hihc20 ️ Conference vs. journal: choosing the right vehicle Conferences prize speed: decision to publication can be mere months, papers are concise, and novelty is king. Journals prize depth: multiple revision rounds, no strict length cap, and a focus on long term influence. When a conference is smarter 🧪 Fresh prototypes or phenomena that need rapid peer feedback Face-to-face networking with collaborators and recruiters ️ Time-sensitive results where a decision within months matters 🧭 When a journal pays off Data and theory fully polished and deserving full exposition Citation slow burn for tenure or promotion dossiers Ready for iterative reviews to reach an authoritative version Take-away If CHI is the main stage , UIST, SIGGRAPH, MobileHCI, CSCW & DIS are the satellite arenas ️; TOCHI, IJHCS, CHB & IJHCI serve as deep archives . Match your study’s maturity, urgency and career goals to the venue, follow the links above, and—once you’ve dropped in those shiny images—let the best audience discover your work. Happy submitting!
• Web, Multimedia & Information Retrieval

  Anything around peer review for conferences such as SIGIR, WWW, ICMR, ICME, ECIR, ICASSP and ACM MM.

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  Recently, I’ve seen many posts on Xiaohongshu about ICME proxy presentations being withdrawn: [image: 1755077313318-icme-proxy-ban.jpg] This paper was submitted by a proxy presenter (i.e., not the actual author/speaker). However, the proxy did not obtain prior approval from the session chair before the presentation. According to the official ICME 2025 policy (https://2025.ieeeicme.org/conference-policies/ “A proxy presenter must request approval from the session chair in advance. After obtaining approval, the proxy presenter must explicitly state in the submitted paper who they are replacing, and this information must be provided to all authors and published on the ICME 2025 website. Failure to comply with the proxy presentation policy will result in your paper not being published in IEEE Xplore. If you believe this decision is in error, you may contact skmanna@conferencecatalysts.com by July 31, 2025, providing detailed information about your situation. Failure to respond by this date will be considered as accepting the decision. The ICME 2025 organizing committee will make the final decision on publication in IEEE Xplore after reviewing your feedback. You will be notified of the outcome via email. If you fail to respond within the deadline, the decision to withdraw your paper will be final, and you will need to contact IEEE Xplore directly for further inquiries.” Some people say ICME has turned into a “paper slaughterhouse” — better not to organize it at all. ICME shouldn’t be held anymore; it’s a paper slaughterhouse. Even if you send a proxy for a poster or oral, your paper won’t get published?? This is just killing off early-career researchers who saved up to attend the conference. Others say this is the right way to run a conference: This is correct. For such conferences, authors should attend in person — to present and also visit the location. Using proxies, especially en masse, just turns the conference into an online mess with no real engagement. Personally, I think finding a proxy presenter can be reasonable, especially for researchers in China who often face serious visa and financial constraints. If the conference clearly stated in the submission phase that proxies are not allowed, then authors should follow the rules. However, if there was no clear policy stated during submission and the rule was enforced only later, then it’s quite unfair. What do you think?
• High Performance Computing

  Anything around peer review for conferences such as ISCA, FAST, ASPLOS, EuroSys, HPCA, SIGMETRICS, FPGA and MICRO.

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  R.I.P. USENIX ATC ...