authors
authors on Beyond Market Intelligence: a running collection of 10 stories we have gathered and hand-picked because they are worth your time. Every post here touches on authors in some way — the news, the analysis, the deep dives, and the occasional surprise find. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work with data. New stories are added to this page as we find them, so check back if you want to keep up with what is happening around authors, or subscribe to the RSS feed to get them as soon as they are published. Browse the collection below, or head back to the homepage to see everything Beyond Market Intelligence is covering right now.
Authors push back as publishers and agents make claims on Anthropic settlement
Authors are voicing concerns as publishers and agents negotiate payouts from Anthropic’s recent settlement, alleging publishers are seeking a disproportionate share of the funds. This development highlights ongoing tensions surrounding AI’s impact on creative industries. The dispute underscores a broader debate about fair compensation for intellectual property used in AI training. For a deeper dive into the evolving landscape of AI and copyright, explore our article, "Seattle Times and Newsday are the latest publications to sue OpenAI and Microsoft."
I regret reviewing for AAAI [D]
Reviewing for prestigious conferences like AAAI can feel like a significant time investment, particularly when reciprocity isn’t guaranteed. A recent Reddit post articulated a common sentiment: the allure of feeling valued can outweigh the practical realities of dedicating time to evaluating work that doesn’t directly benefit one's own submissions.
BMVC 2026 IJCV recommendation? [D]
Navigating the BMVC to *IJCV* special issue recommendation process can be complex. Recommendations aren't solely based on review scores; the Area Chairs and Program Chairs consider factors like oral or highlight selection and nuanced reviewer feedback. Currently, there’s no way to proactively determine if a paper has been recommended—authors are notified via a separate communication. For deeper insights into AI research replication, consider our recent piece on Inherent and their AI agent, Faraday, which recently outperformed leading models.
AAAI 2027 Reviewer Bidding and Assignment Integrity [D]
Recent concerns regarding reviewer collusion at AAAI 2027, particularly within two-cycle review assignments, highlight a critical challenge in maintaining research integrity. The prevalence of submissions from a single geographic region increases the likelihood of these problematic pairings, potentially enabling unethical behavior.
Is it legal to train AI models on copyrighted books? It’s complicated
The legality of training AI models on copyrighted books presents a complex and evolving challenge. Many published authors, often unknowingly, have contributed to the datasets powering AI tools now poised to impact their profession. The question of whether this constitutes infringement is at the heart of ongoing debate. While the situation seems inherently problematic, definitive legal answers remain elusive. For deeper insights into related discussions surrounding AI and investment, explore our article, "Will the DOJ’s investigation into a16z spook other VCs?".
How to file a complaint about a published CVPR paper? [R]
Concerns regarding unfulfilled data release promises in published CVPR papers are increasingly relevant. If a CVPR paper’s core contribution—a dataset—remains unavailable despite conference requirements and author commitments (such as an empty GitHub repository), a formal complaint is warranted. The process isn’t always clear, but it’s essential to ensure accountability and maintain research integrity. Explore the CVPR website and conference guidelines for specific complaint procedures; a lack of dataset availability undermines the validity of the research.
NeurIPS 2026 Concept & Feasibility Track [D]
Navigating the NeurIPS 2026 Concept & Feasibility (C&F) Track presents unique challenges, particularly regarding reviewer engagement. Initial submissions often receive praise for originality, yet concerns about experimental scope—a permissible outcome per track guidelines—can stall progress. A recent discussion highlights a concerning lack of reviewer response even after rebuttal, raising questions about the track’s visibility and author experiences. Explore insights from fellow researchers and a deeper analysis of post-rebuttal score distributions, as detailed in our "NeurIPS 2026 post-rebuttal score distribution poll."
Completely dead NeurIPS review period from both ends? [D]
A concerning trend has emerged during the NeurIPS review period: unusually prolonged silence from both reviewers and authors. Reports indicate reviewers abandoning the process post-initial reviews, while authors remain unresponsive even without submitting rebuttals. This phenomenon, observed across multiple submissions, raises questions about shifts in academic publishing practices—potentially a strategy of widespread submission with limited follow-through. As noted in a related discussion on score tracking post-rebuttal for theory papers, NeurIPS 2026, maintaining engagement throughout the review cycle remains crucial.
No rebuttals from neurips authors [D]
Many NeurIPS authors are experiencing frustration with a lack of reviewer responses, a sentiment echoed in recent discussions. It appears the absence of author rebuttals is surprisingly common; a significant number of submissions, including borderline papers with positive Area Chair feedback, haven't received them. This leaves authors understandably perplexed. While challenging, this situation highlights a broader issue within the peer review process. For deeper insights into related concerns, explore our article, "neurips 2026: ACs and reviewers have disappeared."
NeurIPS 2026 AI-generated reviews [D]
The NeurIPS 2026 paper on AI-generated reviews has sparked considerable debate, particularly regarding the ethics of leveraging LLMs in the peer-review process. Author /u/bricklerex raises a critical point: beyond the study itself, what action is being taken to address potentially problematic AI-assisted reviews? While outright plagiarism is unlikely, concerns exist about superficial engagement with submitted work and the potential for meta-reviewers also utilizing LLMs. For a deeper understanding of the NeurIPS meta-reviewer system, explore "How exactly does the NeurIPS meta reviewer response work?"