scores
scores on Beyond Market Intelligence: a running collection of 7 stories we have gathered and hand-picked because they are worth your time. Every post here touches on scores 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 scores, 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.
*ACL Findings or TMLR? [D]
Navigating the conference publication landscape presents a strategic challenge. With NeurIPS appearing unlikely given current scores, the decision between Transactions on Machine Learning Research (TMLR) and *ACL Findings* warrants careful consideration. While both venues offer visibility, *ACL Findings* likely presents a higher probability of acceptance. Genuinely curious about industry perspectives: would you prioritize *ACL Findings* or TMLR on your publication record? For deeper insights into related AI discovery research, explore our article on "Autonomous Mathematical Discovery in an Open-World Multi-Agent Environment."
NeurIPS 2026 Acceptance Calculator [P]
Navigating NeurIPS submissions can feel daunting. To help demystify the process, we’ve developed a NeurIPS 2026 Acceptance Calculator [P], a small model estimating acceptance probability based on scores and a projected acceptance rate. Explore it here: https://levilingsch.github.io/neurips-acceptance-estimator/. This tool offers a practical way to assess your submission's potential. For researchers looking to bolster their writing skills alongside their technical contributions, our "Best ML papers to pick up writing skills [D]" article provides valuable guidance.
Rejected at EMNLP with decent scores. What can be done next? [D]
Facing rejection at EMNLP, even with promising scores (average 2.83), can be disheartening, especially for a first-time solo author. The key now is strategic action. Prioritize resubmission to ACL Rolling Review (ARR) to leverage existing reviewer feedback—though anticipate new assignments. Given your need for timely publication for internships, a swift ARR resubmission is likely the most effective path. Consider how low-capacity networks can acquire fine-grained scoring, as explored in "Estimating from No Data: Deriving a Continuous Score from Categories," for potential avenues of improvement.
NeurIPS 2026 Main Track — Theory papers score tracking post Rebuttal [D]
Following the NeurIPS 2026 rebuttal period, a discussion has emerged regarding Theory paper score distributions. Early reports suggest scores may be trending lower across disciplines this year. To facilitate a clearer understanding of the landscape, authors are invited to share their scores (x/x/x), confidence levels (x/x/x), and whether scores shifted post-rebuttal, optionally specifying the broad area of research. One author reported a 4/4/4 score with 3/3/3 confidence.
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."
Bad but typical NeurIPS experience? [D]
The NeurIPS review process, as highlighted by one researcher's experience, can be a frustrating lottery. Despite conscientious reviewing and generous scoring, unexpectedly harsh reviews and unresponsive area chairs created a deeply discouraging experience. Adversarial reviewer feedback, coupled with a late-stage AC response, underscored the system’s inherent unpredictability and potential toxicity. This highlights a broader issue within the AI research community, prompting discussions around reviewer accountability—as explored in articles like "NeurIPS 2026: If the rebuttal addresses your concern, please raise your score."
Question about NeurIPS discussion phase [D]
Navigating the NeurIPS discussion phase can be unpredictable. A common question arises: how often do reviewers update scores after indicating concerns are resolved? Experience suggests it’s less frequent than one might hope, particularly when initial engagement is limited. You're not alone in observing this—others have noted similar patterns. Our community has explored this dynamic further in "Conference Reviews: Asking Too Much?" As your case demonstrates, persistence can yield results, ultimately leading to score adjustments.