{"total":53,"rows":[{"id":"2501.10326","title":"Large language models for automated scholarly paper review: A survey","created":"2025-01-17","cited_by_count":61,"area":null},{"id":"2505.07920","title":"Re2: A Consistency-ensured Dataset for Full-stage Peer Review and Multi-turn Rebuttal Discussions","created":"2025-05-12","cited_by_count":23,"area":null},{"id":"2511.16931","title":"OmniScientist: Toward a Co-evolving Ecosystem of Human and AI Scientists","created":"2025-11-21","cited_by_count":18,"area":null},{"id":"2510.08867","title":"ReviewerToo: Should AI Join The Program Committee? A Look At The Future of Peer Review","created":"2025-10-09","cited_by_count":16,"area":null},{"id":"2507.23276","title":"How Far Are AI Scientists from Changing the World?","created":"2025-07-31","cited_by_count":15,"area":null},{"id":"2511.21843","title":"FLAWS: A Benchmark for Error Identification and Localization in Scientific Papers","created":"2025-11-26","cited_by_count":14,"area":null},{"id":"2605.03202","title":"Stop Automating Peer Review Without Rigorous Evaluation","created":"2026-05-04","cited_by_count":14,"area":null},{"id":"2508.10795","title":"Beyond \"Not Novel Enough\": Enriching Scholarly Critique with LLM-Assisted Feedback","created":"2025-08-14","cited_by_count":12,"area":null},{"id":"2605.18661","title":"AI for Auto-Research: Roadmap & User Guide","created":"2026-05-18","cited_by_count":11,"area":null},{"id":"2503.01424","title":"From Hypothesis to Publication: A Comprehensive Survey of AI-Driven Research Support Systems","created":"2025-03-03","cited_by_count":8,"area":null},{"id":"2605.16616","title":"MLReplicate: Benchmarking Autonomous Research Systems for Machine Learning Reproducibility","created":"2026-05-15","cited_by_count":8,"area":null},{"id":"2604.11543","title":"NovBench: Evaluating Large Language Models on Academic Paper Novelty Assessment","created":"2026-04-13","cited_by_count":7,"area":null},{"id":"2512.22145","title":"Pre-review to Peer review: Pitfalls of Automating Reviews using Large Language Models","created":"2025-12-14","cited_by_count":6,"area":null},{"id":"2601.15715","title":"RebuttalAgent: Strategic Persuasion in Academic Rebuttal via Theory of Mind","created":"2026-01-22","cited_by_count":6,"area":null},{"id":"2604.27924","title":"Can AI Be a Good Peer Reviewer? A Survey of Peer Review Process, Evaluation, and the Future","created":"2026-04-30","cited_by_count":6,"area":null},{"id":"2509.25179","title":"NAIPv2: Debiased Pairwise Learning for Efficient Paper Quality Estimation","created":"2025-09-29","cited_by_count":4,"area":null},{"id":"2512.09443","title":"A Human-AI Collaborative Workflow for Mathematical Discovery: A Case Study in Grover-Compatible Riemannian Optimization","created":"2025-12-10","cited_by_count":4,"area":null},{"id":"2601.22638","title":"ScholarPeer: A Context-Aware Multi-Agent Framework for Automated Peer Review","created":"2026-01-30","cited_by_count":4,"area":null},{"id":"2505.14376","title":"Graph-Guided Passage Retrieval for Author-Centric Structured Feedback","created":"2025-05-20","cited_by_count":3,"area":null},{"id":"2508.11310","title":"SGSimEval: A Comprehensive Multifaceted and Similarity-Enhanced Benchmark for Automatic Survey Generation Systems","created":"2025-08-15","cited_by_count":3,"area":null},{"id":"2510.16549","title":"ReviewGuard: Enhancing Deficient Peer Review Detection via LLM-Driven Data Augmentation","created":"2025-10-18","cited_by_count":3,"area":null},{"id":"2604.19502","title":"Beyond Rating: A Comprehensive Evaluation and Benchmark for AI Reviews","created":"2026-04-21","cited_by_count":3,"area":null},{"id":"2606.10159","title":"Gaming AI-Assisted Peer Reviews Poses New Risks to the Scientific Community","created":"2026-06-08","cited_by_count":3,"area":null},{"id":"2511.10902","title":"Multimodal Peer Review Simulation with Actionable To-Do Recommendations for Community-Aware Manuscript Revisions","created":"2025-11-14","cited_by_count":2,"area":null},{"id":"2604.19998","title":"What Makes a Good AI Review? Concern-Level Diagnostics for AI Peer Review","created":"2026-04-21","cited_by_count":2,"area":null},{"id":"2608.00005","title":"RubricReviewer: From Direct Critique to Objective and Comprehensive Rubric-Driven Peer Review","created":"2026-06-04","cited_by_count":2,"area":null},{"id":"2608.01666","title":"Style Wins, Substance Loses: A Diagnosis of LLM-as-Judge in Idea Generation","created":"2026-08-03","cited_by_count":2,"area":null},{"id":"2602.06054","title":"Are We Truly Innovating? A Qualitative and Quantitative Study of Originality in AI Research Papers","created":"2026-01-14","cited_by_count":1,"area":null},{"id":"2602.15849","title":"IntelliAsk: Learning to Ask High-Quality Research Questions via RLVR","created":"2026-01-23","cited_by_count":1,"area":null},{"id":"2603.06862","title":"Supporting Artifact Evaluation with LLMs: A Study with Published Security Research Papers","created":"2026-03-06","cited_by_count":1,"area":null},{"id":"2604.14162","title":"Decoupling Scores and Text: The Politeness Principle in Peer Review","created":"2026-03-23","cited_by_count":1,"area":null},{"id":"2605.28897","title":"Review Arcade: On the Human Alignment and Gameability of LLM Reviews","created":"2026-05-27","cited_by_count":1,"area":null},{"id":"2606.07936","title":"Illusions of the Gold Standard: A Large-scale Analysis of Human Evaluation Protocols for Long-form Text Generation","created":"2026-06-06","cited_by_count":1,"area":null},{"id":"2606.30578","title":"Uncertainty-Aware Generation and Decision-Making Under Ambiguity","created":"2026-06-29","cited_by_count":1,"area":null},{"id":"2607.26066","title":"Do Methods Support the Claims? Intra-Paper Verification for Peer Review","created":"2026-06-21","cited_by_count":1,"area":null},{"id":"2608.03659","title":"How Closely Do LLM Reviews Align with Human Peer Review?","created":"2026-08-04","cited_by_count":1,"area":null},{"id":"2608.12788","title":"ARAC: Benchmarking Auto-Research's Alignment and Completeness on End-to-End Researchs","created":"2026-08-13","cited_by_count":1,"area":null},{"id":"2509.20805","title":"Few-Shot and Training-Free Review Generation via Conversational Prompting","created":"2025-09-25","cited_by_count":0,"area":null},{"id":"2602.06078","title":"Allocate Marginal Reviews to Borderline Papers Using LLM Comparative Ranking","created":"2026-02-04","cited_by_count":0,"area":null},{"id":"2603.20214","title":"Beyond Detection: Governing GenAI in Academic Peer Review as a Sociotechnical Challenge","created":"2026-03-02","cited_by_count":0,"area":null},{"id":"2606.15887","title":"Intelligence Is Not the Bottleneck: Validating an LLM First-Pass Manuscript Score Against Peer-Review Outcomes","created":"2026-06-14","cited_by_count":0,"area":null},{"id":"2606.19051","title":"Which Sections of a Research Paper Best Reveal Its Research Methods? Evidence from Library and Information Science","created":"2026-06-17","cited_by_count":0,"area":null},{"id":"2606.23233","title":"Judgment-Grounded Expansion for Peer Review Generation","created":"2026-06-22","cited_by_count":0,"area":null},{"id":"2607.22681","title":"From peer review nuances to best practices","created":"2026-07-12","cited_by_count":0,"area":null},{"id":"2609.05788","title":"More Than Mimicking Reviewers: Evaluating LLMs for Pre-Submission Peer Review","created":"2026-09-05","cited_by_count":0,"area":null},{"id":"2609.05947","title":"Beyond Final Decisions: A Process-Centric Benchmark for Transparent AI-Assisted Peer Review","created":"2026-09-05","cited_by_count":0,"area":null},{"id":"2609.09076","title":"ActReview: Rebuttal-Guided Training Data and Rubric Rewards for Actionable Peer Review Generation","created":"2026-09-08","cited_by_count":0,"area":null},{"id":"2609.14738","title":"AppliedScientist: Automated Scientific Revision Through Iterative AI Reviewing","created":"2026-09-13","cited_by_count":0,"area":null},{"id":"2609.22805","title":"One Reference or Many? Rethinking Multi-Reference Training for Intermediate-Entropy Text Generation","created":"2026-09-19","cited_by_count":0,"area":null},{"id":"2609.24028","title":"When Evidence Conflicts: Reliability-aware Meta-review Generation","created":"2026-09-21","cited_by_count":0,"area":null},{"id":"2609.37097","title":"Breaking the Illusion of Review Reliability under Static Evaluation: SCOPE Fuzzing for LLM-based Scientific Reviewers","created":"2026-09-29","cited_by_count":0,"area":null},{"id":"2609.39027","title":"A Missing Piece for Trustworthy AI Reviewers: From Benchmarking Rhetorical Robustness to SciCore Review","created":"2026-09-30","cited_by_count":0,"area":null},{"id":"2610.00531","title":"Science or Slop?: Benchmarking and Mitigating Scientific Slop in AI-Generated Papers","created":"2026-09-30","cited_by_count":0,"area":null}],"next_cursor":null}