{"total":84,"rows":[{"id":"2607.24653","title":"Kimi K3: Open Frontier Intelligence","created":"2026-07-27","cited_by_count":138,"area":"agents"},{"id":"2601.08536","title":"DeepResearch Bench II: Diagnosing Deep Research Agents via Rubrics from Expert Reports","created":"2026-01-13","cited_by_count":34,"area":"agents"},{"id":"2604.13602","title":"Reward Hacking in the Era of Large Models: Mechanisms, Emergent Misalignment, Challenges","created":"2026-04-15","cited_by_count":33,"area":"alignment"},{"id":"2605.12474","title":"Reward Hacking in Rubric-Based Reinforcement Learning","created":"2026-05-12","cited_by_count":26,"area":"alignment"},{"id":"2512.04324","title":"DAComp: Benchmarking Data Agents across the Full Data Intelligence Lifecycle","created":"2025-12-03","cited_by_count":23,"area":"agents"},{"id":"2512.14865","title":"Audio MultiChallenge: A Multi-Turn Evaluation of Spoken Dialogue Systems on Natural Human Interaction","created":"2025-12-16","cited_by_count":19,"area":null},{"id":"2602.03619","title":"Learning Query-Specific Rubrics from Human Preferences for DeepResearch Report Generation","created":"2026-02-03","cited_by_count":18,"area":"alignment"},{"id":"2604.11753","title":"Agentic Aggregation for Parallel Scaling of Long-Horizon Agentic Tasks","created":"2026-04-13","cited_by_count":18,"area":"lr"},{"id":"2606.12507","title":"Rubric-Guided Self-Distillation: Post-Training Without Rubric Verifiers","created":"2026-06-10","cited_by_count":15,"area":"distill"},{"id":"2602.11685","title":"DRACO: a Cross-Domain Benchmark for Deep Research Accuracy, Completeness, and Objectivity","created":"2026-02-12","cited_by_count":14,"area":null},{"id":"2512.17776","title":"DEER: A Benchmark for Evaluating Deep Research Agents on Expert Report Generation","created":"2025-12-19","cited_by_count":12,"area":"agents"},{"id":"2512.20491","title":"Step-DeepResearch Technical Report","created":"2025-12-23","cited_by_count":12,"area":null},{"id":"2603.20882","title":"RubricRAG: Towards Interpretable and Reliable LLM Evaluation via Domain Knowledge Retrieval for Rubric Generation","created":"2026-03-21","cited_by_count":11,"area":null},{"id":"2605.24218","title":"QUEST: Training Frontier Deep Research Agents with Fully Synthetic Tasks","created":"2026-05-22","cited_by_count":11,"area":"agents"},{"id":"2607.22083","title":"Nanbeige4.2-3B: Unlocking Agentic Capabilities in a Compact Model","created":"2026-07-24","cited_by_count":11,"area":"agents"},{"id":"2603.05912","title":"DeepFact: Co-Evolving Benchmarks and Agents for Deep Research Factuality","created":"2026-03-06","cited_by_count":10,"area":"agents"},{"id":"2604.02795","title":"Rubrics to Tokens: Bridging Response-level Rubrics and Token-level Rewards in Instruction Following Tasks","created":"2026-04-03","cited_by_count":10,"area":"alignment"},{"id":"2605.19196","title":"Time to REFLECT: Can We Trust LLM Judges for Evidence-based Research Agents?","created":"2026-05-18","cited_by_count":10,"area":"agents"},{"id":"2511.22978","title":"ShoppingComp: Are LLMs Really Ready for Your Shopping Cart?","created":"2025-11-28","cited_by_count":9,"area":null},{"id":"2602.13855","title":"From Fluent to Verifiable: Claim-Level Auditability for Deep Research Agents","created":"2026-02-14","cited_by_count":7,"area":"agents"},{"id":"2602.18940","title":"DREAM: Deep Research Evaluation with Agentic Metrics","created":"2026-02-21","cited_by_count":7,"area":"agents"},{"id":"2605.26958","title":"Tournament-GRPO: Group-Wise Tournament Rewards for Reinforcement Learning in Open-Ended Long-Form Generation","created":"2026-05-26","cited_by_count":7,"area":"lr"},{"id":"2605.31433","title":"SCOPE: Self-Play via Co-Evolving Policies for Open-Ended Tasks","created":"2026-05-29","cited_by_count":7,"area":"synth"},{"id":"2606.29920","title":"Can LLM-as-a-Judge Reliably Verify Rubrics in Agentic Scenarios?","created":"2026-06-29","cited_by_count":7,"area":"agents"},{"id":"2602.18458","title":"The Story is Not the Science: Execution-Grounded Evaluation of Mechanistic Interpretability Research","created":"2026-02-05","cited_by_count":6,"area":"mechinterp"},{"id":"2605.08366","title":"SWE Atlas: Benchmarking Coding Agents Beyond Issue Resolution","created":"2026-05-08","cited_by_count":6,"area":"agents"},{"id":"2607.12835","title":"Can LLMs Write Reliable Rubrics? A Meta-Evaluation for Experiment Reproduction","created":"2026-07-14","cited_by_count":6,"area":"agents"},{"id":"2603.06942","title":"Deep Research, Shallow Evaluation: A Case Study in Meta-Evaluation for Long-Form QA Benchmarks","created":"2026-03-06","cited_by_count":5,"area":null},{"id":"2603.18516","title":"Total Recall QA: A Verifiable Evaluation Suite for Deep Research Agents","created":"2026-03-19","cited_by_count":5,"area":"agents"},{"id":"2605.25240","title":"JudgmentBench: Comparing Rubric and Preference Evaluation for Quality Assessment","created":"2026-05-24","cited_by_count":5,"area":null},{"id":"2606.15367","title":"S1-DeepResearch: Beyond Search, Toward Real-World Long-Horizon Research Agents","created":"2026-06-13","cited_by_count":5,"area":"agents"},{"id":"2601.13217","title":"Beyond Single-shot Writing: Deep Research Agents are Unreliable at Multi-turn Report Revision","created":"2026-01-19","cited_by_count":4,"area":"agents"},{"id":"2605.09730","title":"RubricRefine: Improving Tool-Use Agent Reliability with Training-Free Pre-Execution Refinement","created":"2026-05-10","cited_by_count":4,"area":null},{"id":"2605.29790","title":"Evolve as a Team: Collaborative Self-Evolution for LLM-based Multi-Agent Systems","created":"2026-05-28","cited_by_count":4,"area":"agents"},{"id":"2606.01075","title":"On the Generalization Gap in Self-Evolving Language Model Reasoning","created":"2026-05-31","cited_by_count":4,"area":"lr"},{"id":"2606.03361","title":"Mitigating False Credit Propagation: Probabilistic Graphical Reward Aggregation for Rubric-Based Reinforcement Learning","created":"2026-06-02","cited_by_count":4,"area":"alignment"},{"id":"2606.08625","title":"From Holistic Evaluation to Structured Criteria: Rubrics Across the Evolving LLM Landscape","created":"2026-06-07","cited_by_count":4,"area":null},{"id":"2606.17029","title":"DEEPRUBRIC: Evidence-Tree Rubric Supervision for Efficient Reinforcement Learning of Deep Research Agents","created":"2026-06-15","cited_by_count":4,"area":"lr"},{"id":"2608.11683","title":"FrontierFinance: A Challenging Benchmark for Measuring Frontier Intelligence of Finance Agents","created":"2026-08-12","cited_by_count":4,"area":"agents"},{"id":"2601.12369","title":"Can Deep Research Agents Retrieve and Organize? Evaluating the Synthesis Gap with Expert Taxonomies","created":"2026-01-18","cited_by_count":3,"area":"agents"},{"id":"2603.22744","title":"LH-Bench: Skill-Grounded Evaluation of Long-Horizon Agents on Subjective Enterprise Tasks","created":"2026-03-24","cited_by_count":3,"area":"agents"},{"id":"2604.01375","title":"The Hitchhikers Guide to Rubric Quality Understanding and Enrichment","created":"2026-04-01","cited_by_count":3,"area":null},{"id":"2608.27505","title":"A Survey on Rubric-Guided Reinforcement Learning for Language Models","created":"2026-08-27","cited_by_count":3,"area":"alignment"},{"id":"2609.02942","title":"Judging LLM-as-a-Judge: Concerning Rubric Artifacts in LLM-based Automated Text Generation Evaluation","created":"2026-08-31","cited_by_count":3,"area":null},{"id":"2604.02988","title":"Self-Optimizing Multi-Agent Systems for Deep Research","created":"2026-04-03","cited_by_count":2,"area":null},{"id":"2605.30907","title":"BlueFin: Benchmarking LLM Agents on Financial Spreadsheets","created":"2026-05-29","cited_by_count":2,"area":"agents"},{"id":"2607.19322","title":"Two-Level Meta-Rubrics for Evaluating Open-Ended Generation: GAMUT, a Benchmark for Factual Completeness","created":"2026-07-21","cited_by_count":2,"area":null},{"id":"2607.27853","title":"FinanceHarness: Autonomous Financial Deep Research Framework","created":"2026-07-30","cited_by_count":2,"area":"agents"},{"id":"2608.21601","title":"K-Bench: measuring model performance on real scientific agent requests","created":"2026-08-21","cited_by_count":2,"area":"agents"},{"id":"2601.22735","title":"MM-THEBench: Do Reasoning MLLMs Think Reasonably?","created":"2026-01-30","cited_by_count":1,"area":"lr"},{"id":"2602.01590","title":"Wiki Live Challenge: Challenging Deep Research Agents with Expert-Level Wikipedia Articles","created":"2026-02-02","cited_by_count":1,"area":"agents"},{"id":"2602.15019","title":"Hunt Globally: Wide Search AI Agents for Drug Asset Scouting in Investing, Business Development, and Competitive Intelligence","created":"2026-02-16","cited_by_count":1,"area":"agents"},{"id":"2603.01343","title":"PanCanBench: A Comprehensive Benchmark for Evaluating Large Language Models in Pancreatic Oncology","created":"2026-03-02","cited_by_count":1,"area":null},{"id":"2604.14683","title":"DR$^{3}$-Eval: Towards Realistic and Reproducible Deep Research Evaluation","created":"2026-04-16","cited_by_count":1,"area":"agents"},{"id":"2604.18418","title":"MedProbeBench: Systematic Benchmarking at Deep Evidence Integration for Expert-level Medical Guideline","created":"2026-04-20","cited_by_count":1,"area":null},{"id":"2604.23815","title":"DRACULA: Hunting for the Actions Users Want Deep Research Agents to Execute","created":"2026-04-26","cited_by_count":1,"area":"agents"},{"id":"2605.12131","title":"Rollout Cards: A Reproducibility Standard for Agent Research","created":"2026-05-12","cited_by_count":1,"area":"lr"},{"id":"2605.17554","title":"Evaluating Deep Research Agents on Expert Consulting Work: A Benchmark with Verifiers, Rubrics, and Cognitive Traps","created":"2026-05-17","cited_by_count":1,"area":"agents"},{"id":"2605.27882","title":"VibeSearchBench: Benchmarking Long-horizon Proactive Search in the Wild","created":"2026-05-27","cited_by_count":1,"area":"agents"},{"id":"2606.28322","title":"PerceptionRubrics: Calibrating Multimodal Evaluation to Human Perception","created":"2026-06-26","cited_by_count":1,"area":null},{"id":"2608.18931","title":"Test-Time Scaling in the Wild: Why Exploitation, Not Exploration, Is the Bottleneck","created":"2026-08-19","cited_by_count":1,"area":"lr"},{"id":"2609.01294","title":"Explore Before Committing: Hypothesis-Guided Search for Deep Research Agents","created":"2026-09-01","cited_by_count":1,"area":"agents"},{"id":"2610.13303","title":"Agreement Without Alignment: Label-Free Rubric Clarification Increases LLM-Judge Consensus but Not Agreement with Humans","created":"2026-10-09","cited_by_count":1,"area":null},{"id":"2604.12967","title":"Cycle-Consistent Search: Question Reconstructability as a Proxy Reward for Search Agent Training","created":"2026-04-14","cited_by_count":0,"area":"lr"},{"id":"2604.14518","title":"Mind DeepResearch Technical Report","created":"2026-04-16","cited_by_count":0,"area":null},{"id":"2605.04356","title":"Efficiently Aligning Language Models with Online Natural Language Feedback","created":"2026-05-05","cited_by_count":0,"area":"alignment"},{"id":"2606.07040","title":"Beyond Rubrics: Exploration-Guided Evaluation Skills for Reward Modeling","created":"2026-06-05","cited_by_count":0,"area":"alignment"},{"id":"2606.09748","title":"Multi-Turn Evaluation of Deep Research Agents Under Process-Level Feedback","created":"2026-06-08","cited_by_count":0,"area":"agents"},{"id":"2606.12871","title":"DailyReport: An Open-ended Benchmark for Evaluating Search Agents on Daily Search Tasks","created":"2026-06-11","cited_by_count":0,"area":"agents"},{"id":"2608.02163","title":"From Simple QA to Deep Research: A Verifiable Benchmark Constructed through Iterative Task Evolution","created":"2026-08-03","cited_by_count":0,"area":null},{"id":"2608.21376","title":"On the Role of Citations in Preference Data","created":"2026-07-06","cited_by_count":0,"area":"alignment"},{"id":"2608.28643","title":"Redesigning and Auditing Deep Research Writing for Faithful Reports","created":"2026-08-12","cited_by_count":0,"area":null},{"id":"2608.31076","title":"Learning to Evaluate Before Improving: Automatic Rubric Induction for Automatic Research Agents","created":"2026-08-31","cited_by_count":0,"area":"agents"},{"id":"2609.01058","title":"ARISE-RL: Agentic Rubric-Grounded Iterative Self-Evolution with Reinforcement Learning","created":"2026-09-01","cited_by_count":0,"area":"agents"},{"id":"2609.11243","title":"Sci-MMR: Benchmarking Multi-Step Evidence-Grounded Scientific Reasoning in Multimodal Agents","created":"2026-09-10","cited_by_count":0,"area":"lr"},{"id":"2609.17326","title":"From Transient Prompts to Persistent Control: Scientific Poster Generation via Recursive Semantic-Geometric Contracts","created":"2026-09-15","cited_by_count":0,"area":null},{"id":"2609.30604","title":"The Hard Part Comes After Search: Benchmarking Web Agents on Synthesizing, Organizing, and Displaying Knowledge","created":"2026-09-24","cited_by_count":0,"area":"agents"},{"id":"2609.34296","title":"Dr.Credit: Rubric-Grounded Process Credit Assignment for Deep Research Agents","created":"2026-09-28","cited_by_count":0,"area":"agents"},{"id":"2609.36071","title":"LongCat-DeepResearch Technical Report","created":"2026-09-28","cited_by_count":0,"area":null},{"id":"2610.00374","title":"Faithful Chart Generation for Multimodal Deep Research: Frame-Evidence Co-Adaptation","created":"2026-09-30","cited_by_count":0,"area":null},{"id":"2610.09569","title":"RELATE: An Evaluation Framework for measuring Relational Orientation of Large Language Models","created":"2026-10-07","cited_by_count":0,"area":null},{"id":"2610.10809","title":"Evaluating Rubric Generation with Interventional Transfer","created":"2026-10-07","cited_by_count":0,"area":null},{"id":"2610.18092","title":"LifeSearch: Benchmarking Deep Research Agents for Real-World Life and Productivity","created":"2026-10-13","cited_by_count":0,"area":"agents"},{"id":"2610.19992","title":"SoK: Grading Open-Text Legal Answers, from Law School Exams to Trustworthy Rubric Judges","created":"2026-10-14","cited_by_count":0,"area":null}],"next_cursor":null}