{"total":179,"rows":[{"id":"2501.19393","title":"s1: Simple test-time scaling","created":"2025-01-31","cited_by_count":1341,"area":"lr"},{"id":"2406.11717","title":"Refusal in Language Models Is Mediated by a Single Direction","created":"2024-06-17","cited_by_count":1032,"area":"safety"},{"id":"2507.20534","title":"Kimi K2: Open Agentic Intelligence","created":"2025-07-28","cited_by_count":567,"area":"agents"},{"id":"2502.05171","title":"Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach","created":"2025-02-07","cited_by_count":415,"area":"lr"},{"id":"2409.02060","title":"OLMoE: Open Mixture-of-Experts Language Models","created":"2024-09-03","cited_by_count":301,"area":"moe"},{"id":"2407.01502","title":"AI Agents That Matter","created":"2024-07-01","cited_by_count":219,"area":null},{"id":"2510.26692","title":"Kimi Linear: An Expressive, Efficient Attention Architecture","created":"2025-10-30","cited_by_count":196,"area":"deeprl"},{"id":"2407.01492","title":"RegMix: Data Mixture as Regression for Language Model Pre-training","created":"2024-07-01","cited_by_count":177,"area":null},{"id":"2407.10362","title":"LAB-Bench: Measuring Capabilities of Language Models for Biology Research","created":"2024-07-14","cited_by_count":156,"area":null},{"id":"2409.11363","title":"CORE-Bench: Fostering the Credibility of Published Research Through a Computational Reproducibility Agent Benchmark","created":"2024-09-17","cited_by_count":123,"area":"agents"},{"id":"2511.04703","title":"Measuring what Matters: Construct Validity in Large Language Model Benchmarks","created":"2025-11-03","cited_by_count":119,"area":null},{"id":"2411.12990","title":"BetterBench: Assessing AI Benchmarks, Uncovering Issues, and Establishing Best Practices","created":"2024-11-20","cited_by_count":114,"area":null},{"id":"2406.08446","title":"OLMES: A Standard for Language Model Evaluations","created":"2024-06-12","cited_by_count":106,"area":null},{"id":"2507.09089","title":"Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity","created":"2025-07-12","cited_by_count":101,"area":null},{"id":"2504.07086","title":"A Sober Look at Progress in Language Model Reasoning: Pitfalls and Paths to Reproducibility","created":"2025-04-09","cited_by_count":93,"area":"lr"},{"id":"2408.04667","title":"Non-Determinism of \"Deterministic\" LLM Settings","created":"2024-08-06","cited_by_count":92,"area":null},{"id":"2510.11977","title":"Holistic Agent Leaderboard: The Missing Infrastructure for AI Agent Evaluation","created":"2025-10-13","cited_by_count":92,"area":"agents"},{"id":"2407.04069","title":"A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and Recommendations","created":"2024-07-04","cited_by_count":85,"area":null},{"id":"2502.03540","title":"Path Planning for Masked Diffusion Model Sampling","created":"2025-02-05","cited_by_count":80,"area":"diffusion"},{"id":"2410.16153","title":"Pangea: A Fully Open Multilingual Multimodal LLM for 39 Languages","created":"2024-10-21","cited_by_count":64,"area":"mllm"},{"id":"2502.06559","title":"Can We Trust AI Benchmarks? An Interdisciplinary Review of Current Issues in AI Evaluation","created":"2025-02-10","cited_by_count":60,"area":null},{"id":"2506.05233","title":"MesaNet: Sequence Modeling by Locally Optimal Test-Time Training","created":"2025-06-05","cited_by_count":47,"area":null},{"id":"2406.03368","title":"IrokoBench: A New Benchmark for African Languages in the Age of Large Language Models","created":"2024-06-05","cited_by_count":43,"area":null},{"id":"2503.09543","title":"PolyPythias: Stability and Outliers across Fifty Language Model Pre-Training Runs","created":"2025-03-12","cited_by_count":35,"area":null},{"id":"2406.14325","title":"Reproducibility in Machine Learning-based Research: Overview, Barriers and Drivers","created":"2024-06-20","cited_by_count":34,"area":null},{"id":"2504.16137","title":"Virology Capabilities Test (VCT): A Multimodal Virology Q&A Benchmark","created":"2025-04-21","cited_by_count":31,"area":null},{"id":"2505.10475","title":"Parallel Scaling Law for Language Models","created":"2025-05-15","cited_by_count":30,"area":"lr"},{"id":"2503.01747","title":"Position: Don't Use the CLT in LLM Evals With Fewer Than a Few Hundred Datapoints","created":"2025-03-03","cited_by_count":23,"area":null},{"id":"2504.10191","title":"Localized Cultural Knowledge is Conserved and Controllable in Large Language Models","created":"2025-04-14","cited_by_count":20,"area":"wm"},{"id":"2506.01732","title":"Common Corpus: The Largest Collection of Ethical Data for LLM Pre-Training","created":"2025-06-02","cited_by_count":20,"area":null},{"id":"2506.03133","title":"PoLAR: Polar-Decomposed Low-Rank Adapter Representation","created":"2025-06-03","cited_by_count":20,"area":null},{"id":"2503.02574","title":"LLM-Safety Evaluations Lack Robustness","created":"2025-03-04","cited_by_count":18,"area":"alignment"},{"id":"2512.21852","title":"A Comedy of Estimators: On KL Regularization in RL Training of LLMs","created":"2025-12-26","cited_by_count":18,"area":"lr"},{"id":"2602.07150","title":"On Randomness in Agentic Evals","created":"2026-02-06","cited_by_count":17,"area":"agents"},{"id":"2510.04265","title":"Don't Pass@k: A Bayesian Framework for Large Language Model Evaluation","created":"2025-10-05","cited_by_count":15,"area":"lr"},{"id":"2603.11510","title":"Tiny Aya: Bridging Scale and Multilingual Depth","created":"2026-03-12","cited_by_count":15,"area":null},{"id":"2605.25492","title":"SafetyRepro: Configuration-Conditional Rank Instability on Alignment Benchmarks","created":"2026-05-25","cited_by_count":15,"area":null},{"id":"2506.00777","title":"Improving Automatic Evaluation of Large Language Models (LLMs) in Biomedical Relation Extraction via LLMs-as-the-Judge","created":"2025-06-01","cited_by_count":13,"area":null},{"id":"2510.24963","title":"Language Model Behavioral Phases are Consistent Across Architecture, Training Data, and Scale","created":"2025-10-28","cited_by_count":13,"area":null},{"id":"2503.01483","title":"KurTail : Kurtosis-based LLM Quantization","created":"2025-03-03","cited_by_count":12,"area":null},{"id":"2406.07424","title":"MINERS: Multilingual Language Models as Semantic Retrievers","created":"2024-06-11","cited_by_count":11,"area":null},{"id":"2406.16746","title":"The Responsible Foundation Model Development Cheatsheet: A Review of Tools & Resources","created":"2024-06-24","cited_by_count":11,"area":null},{"id":"2501.06374","title":"AFRIDOC-MT: Document-level MT Corpus for African Languages","created":"2025-01-10","cited_by_count":11,"area":null},{"id":"2504.07825","title":"Who Benchmarks the Benchmarks? Towards Comprehensive Evaluation of Commonsense Reasoning Benchmarks","created":"2025-04-10","cited_by_count":11,"area":"lr"},{"id":"2601.19532","title":"Benchmarks Saturate When The Model Gets Smarter Than The Judge","created":"2026-01-27","cited_by_count":11,"area":null},{"id":"2601.23045","title":"The Hot Mess of AI: How Does Misalignment Scale With Model Intelligence and Task Complexity?","created":"2026-01-30","cited_by_count":10,"area":null},{"id":"2603.01914","title":"AdaPonderLM: Gated Pondering Language Models with Token-Wise Adaptive Depth","created":"2026-03-02","cited_by_count":10,"area":"lr"},{"id":"2410.11672","title":"Leaving the barn door open for Clever Hans: Simple features predict LLM benchmark answers","created":"2024-10-15","cited_by_count":9,"area":null},{"id":"2512.07795","title":"ReasonBENCH: Benchmarking the (In)Stability of LLM Reasoning","created":"2025-12-08","cited_by_count":9,"area":"lr"},{"id":"2504.06536","title":"Lugha-Llama: Adapting Large Language Models for African Languages","created":"2025-04-09","cited_by_count":8,"area":null},{"id":"2504.07749","title":"NorEval: A Norwegian Language Understanding and Generation Evaluation Benchmark","created":"2025-04-10","cited_by_count":8,"area":null},{"id":"2603.13281","title":"ICaRus: Identical Cache Reuse for Efficient Multi Model Inference","created":"2026-02-27","cited_by_count":8,"area":"agents"},{"id":"2605.19537","title":"The Silent Hyperparameter: Quantifying the Impact of Inference Backends on LLM Reproducibility","created":"2026-05-19","cited_by_count":8,"area":null},{"id":"2605.28873","title":"Pre-Registering the Detectable Effect: A Paired-MDE Budget for 4-bit Quantization Benchmarks, with a Pilot Audit","created":"2026-05-25","cited_by_count":8,"area":null},{"id":"2412.08392","title":"The Roles of English in Evaluating Multilingual Language Models","created":"2024-12-11","cited_by_count":7,"area":null},{"id":"2412.11831","title":"Are You Doubtful? Oh, It Might Be Difficult Then! Exploring the Use of Model Uncertainty for Question Difficulty Estimation","created":"2024-12-16","cited_by_count":7,"area":null},{"id":"2502.02289","title":"Evalita-LLM: Benchmarking Large Language Models on Italian","created":"2025-02-04","cited_by_count":7,"area":null},{"id":"2503.03962","title":"On the Acquisition of Shared Grammatical Representations in Bilingual Language Models","created":"2025-03-05","cited_by_count":7,"area":null},{"id":"2506.19882","title":"Position: Machine Learning Conferences Should Establish a \"Refutations and Critiques\" Track","created":"2025-06-24","cited_by_count":7,"area":null},{"id":"2509.11414","title":"Continually Adding New Languages to Multilingual Language Models","created":"2025-09-14","cited_by_count":7,"area":null},{"id":"2509.21623","title":"OjaKV: Context-Aware Online Low-Rank KV Cache Compression","created":"2025-09-25","cited_by_count":7,"area":"inference"},{"id":"2603.00025","title":"TAB-PO: Preference Optimization with a Token-Level Adaptive Barrier for Token-Critical Structured Generation","created":"2026-02-03","cited_by_count":7,"area":"alignment"},{"id":"2406.10366","title":"Improving the Validity and Practical Usefulness of AI/ML Evaluations Using an Estimands Framework","created":"2024-06-14","cited_by_count":6,"area":null},{"id":"2505.20133","title":"Token Distillation: Attention-aware Input Embeddings For New Tokens","created":"2025-05-26","cited_by_count":6,"area":null},{"id":"2510.24626","title":"Relative Scaling Laws for LLMs","created":"2025-10-28","cited_by_count":6,"area":null},{"id":"2601.15812","title":"ErrorMap and ErrorAtlas: Charting the Failure Landscape of Large Language Models","created":"2026-01-22","cited_by_count":6,"area":null},{"id":"2409.06595","title":"GroUSE: A Benchmark to Evaluate Evaluators in Grounded Question Answering","created":"2024-09-10","cited_by_count":5,"area":"rag"},{"id":"2502.04499","title":"Revisiting Intermediate-Layer Matching in Knowledge Distillation: Layer-Selection Strategy Doesn't Matter (Much)","created":"2025-02-06","cited_by_count":5,"area":"distill"},{"id":"2504.16921","title":"IberBench: LLM Evaluation on Iberian Languages","created":"2025-04-23","cited_by_count":5,"area":null},{"id":"2506.18710","title":"Benchmarking the Pedagogical Knowledge of Large Language Models","created":"2025-06-23","cited_by_count":5,"area":null},{"id":"2507.09424","title":"DATE-LM: Benchmarking Data Attribution Evaluation for Large Language Models","created":"2025-07-12","cited_by_count":5,"area":null},{"id":"2511.21437","title":"A Systematic Study of In-the-Wild Model Merging for Large Language Models","created":"2025-11-26","cited_by_count":5,"area":null},{"id":"2605.02209","title":"Submodular Benchmark Selection","created":"2026-05-04","cited_by_count":5,"area":null},{"id":"2407.06483","title":"Composable Interventions for Language Models","created":"2024-07-09","cited_by_count":4,"area":"safety"},{"id":"2412.14471","title":"Why We Build Local Large Language Models: An Observational Analysis from 35 Japanese and Multilingual LLMs","created":"2024-12-19","cited_by_count":4,"area":null},{"id":"2510.14773","title":"Finding Answers in Thought Matters: Revisiting Evaluation on Large Language Models with Reasoning","created":"2025-10-16","cited_by_count":4,"area":"lr"},{"id":"2511.05613","title":"Who Evaluates AI's Social Impacts? Mapping Coverage and Gaps in First and Third Party Evaluations","created":"2025-11-06","cited_by_count":4,"area":null},{"id":"2511.21695","title":"EvalCards: A Framework for Standardized Evaluation Reporting","created":"2025-11-05","cited_by_count":4,"area":null},{"id":"2601.06118","title":"Beyond Reproducibility: Token Probabilities Expose Large Language Model Nondeterminism","created":"2026-01-03","cited_by_count":4,"area":null},{"id":"2606.09809","title":"Evaluation Cards: An Interpretive Layer for AI Evaluation Reporting","created":"2026-06-08","cited_by_count":4,"area":null},{"id":"2610.02076","title":"LLM-as-Jev: LLMs Are Already Jev-Style Decision Models -- When and How to Fine-Tune Them","created":"2026-10-01","cited_by_count":4,"area":null},{"id":"2511.13703","title":"Generalist Foundation Models Are Not Clinical Enough for Hospital Operations","created":"2025-11-17","cited_by_count":3,"area":null},{"id":"2512.04555","title":"ADAPT: Learning Task Mixtures for Budget-Constrained Instruction Tuning","created":"2025-12-04","cited_by_count":3,"area":null},{"id":"2602.13215","title":"When to Think Fast and Slow? AMOR: Adaptive Entropy Gate for Hybrid Models","created":"2026-01-22","cited_by_count":3,"area":null},{"id":"2605.24869","title":"Lngram: N-gram Conditional Memory in Latent Space","created":"2026-05-24","cited_by_count":3,"area":null},{"id":"2606.24020","title":"You Don't Need to Run Every Eval","created":"2026-06-22","cited_by_count":3,"area":null},{"id":"2408.11847","title":"Prompto: An open source library for asynchronous querying of LLM endpoints","created":"2024-08-12","cited_by_count":2,"area":null},{"id":"2411.00593","title":"Adapting Language Models via Token Translation","created":"2024-11-01","cited_by_count":2,"area":null},{"id":"2502.18798","title":"Choices Speak Louder than Questions","created":"2025-02-26","cited_by_count":2,"area":null},{"id":"2503.02334","title":"BiasICL: In-Context Learning and Demographic Biases of Vision Language Models","created":"2025-03-04","cited_by_count":2,"area":"mllm"},{"id":"2504.14039","title":"MEQA: A Meta-Evaluation Framework for Question & Answer LLM Benchmarks","created":"2025-04-18","cited_by_count":2,"area":null},{"id":"2506.06808","title":"Not quite Sherlock Holmes: Language model predictions do not reliably differentiate impossible from improbable events","created":"2025-06-07","cited_by_count":2,"area":null},{"id":"2510.09599","title":"Prompting Test-Time Scaling Is A Strong LLM Reasoning Data Augmentation","created":"2025-10-10","cited_by_count":2,"area":"lr"},{"id":"2510.11278","title":"ENIGMA: The Geometry of Reasoning and Alignment in Large-Language Models","created":"2025-10-13","cited_by_count":2,"area":"lr"},{"id":"2601.05637","title":"GenCtrl -- A Formal Controllability Toolkit for Generative Models","created":"2026-01-09","cited_by_count":2,"area":null},{"id":"2603.14591","title":"FlashHead: Efficient Drop-In Replacement for the Classification Head in Language Model Inference","created":"2026-03-15","cited_by_count":2,"area":null},{"id":"2603.20380","title":"Herding CATs: ALARA for Agent Harness Engineering in Portable Composable Multi-Agent Teams","created":"2026-03-20","cited_by_count":2,"area":null},{"id":"2604.18529","title":"HybridGen: Efficient LLM Generative Inference via CPU-GPU Hybrid Computing","created":"2026-04-20","cited_by_count":2,"area":"inference"},{"id":"2605.29414","title":"Beyond Bilingual Transfer: Multilingual Code-Switching in Instruction Tuning","created":"2026-05-28","cited_by_count":2,"area":null},{"id":"2606.00135","title":"On Effectiveness and Efficiency of Agentic Tool-calling and RL Training","created":"2026-05-28","cited_by_count":2,"area":"agents"}],"next_cursor":"100"}