{"total":116,"rows":[{"id":"2307.10169","title":"Challenges and Applications of Large Language Models","created":"2023-07-19","cited_by_count":254,"area":null},{"id":"2311.04076","title":"Do LLMs exhibit human-like response biases? A case study in survey design","created":"2023-11-07","cited_by_count":180,"area":null},{"id":"2309.13638","title":"Embers of Autoregression: Understanding Large Language Models Through the Problem They are Trained to Solve","created":"2023-09-24","cited_by_count":178,"area":null},{"id":"2411.00816","title":"CycleResearcher: Improving Automated Research via Automated Review","created":"2024-10-28","cited_by_count":148,"area":null},{"id":"2307.03718","title":"Frontier AI Regulation: Managing Emerging Risks to Public Safety","created":"2023-07-06","cited_by_count":98,"area":null},{"id":"2504.08165","title":"Findings of the BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora","created":"2025-04-10","cited_by_count":88,"area":null},{"id":"2310.10638","title":"In-context Pretraining: Language Modeling Beyond Document Boundaries","created":"2023-10-16","cited_by_count":79,"area":null},{"id":"2407.21792","title":"Safetywashing: Do AI Safety Benchmarks Actually Measure Safety Progress?","created":"2024-07-31","cited_by_count":61,"area":null},{"id":"2312.10523","title":"Paloma: A Benchmark for Evaluating Language Model Fit","created":"2023-12-16","cited_by_count":54,"area":null},{"id":"2311.10766","title":"Value FULCRA: Mapping Large Language Models to the Multidimensional Spectrum of Basic Human Values","created":"2023-11-15","cited_by_count":50,"area":null},{"id":"2402.04177","title":"Scaling Laws for Downstream Task Performance of Large Language Models","created":"2024-02-06","cited_by_count":49,"area":null},{"id":"2310.17688","title":"Managing extreme AI risks amid rapid progress","created":"2023-10-26","cited_by_count":48,"area":null},{"id":"2308.01404","title":"Hoodwinked: Deception and Cooperation in a Text-Based Game for Language Models","created":"2023-07-05","cited_by_count":47,"area":null},{"id":"2407.19584","title":"SaulLM-54B & SaulLM-141B: Scaling Up Domain Adaptation for the Legal Domain","created":"2024-07-28","cited_by_count":39,"area":null},{"id":"2310.18362","title":"SoK: Memorization in General-Purpose Large Language Models","created":"2023-10-24","cited_by_count":37,"area":null},{"id":"2310.09139","title":"The Consensus Game: Language Model Generation via Equilibrium Search","created":"2023-10-13","cited_by_count":36,"area":null},{"id":"2404.10830","title":"Fewer Truncations Improve Language Modeling","created":"2024-04-16","cited_by_count":35,"area":null},{"id":"2407.16711","title":"Benchmarks as Microscopes: A Call for Model Metrology","created":"2024-07-22","cited_by_count":35,"area":null},{"id":"2507.00885","title":"Scaling Laws Are Unreliable for Downstream Tasks: A Reality Check","created":"2025-07-01","cited_by_count":29,"area":null},{"id":"2310.11053","title":"Denevil: Towards Deciphering and Navigating the Ethical Values of Large Language Models via Instruction Learning","created":"2023-10-17","cited_by_count":26,"area":null},{"id":"2403.02419","title":"Are More LLM Calls All You Need? Towards Scaling Laws of Compound Inference Systems","created":"2024-03-04","cited_by_count":25,"area":null},{"id":"2310.09753","title":"When can transformers reason with abstract symbols?","created":"2023-10-15","cited_by_count":24,"area":null},{"id":"2401.10463","title":"Critical Data Size of Language Models from a Grokking Perspective","created":"2024-01-19","cited_by_count":24,"area":null},{"id":"2401.00788","title":"Astraios: Parameter-Efficient Instruction Tuning Code Large Language Models","created":"2024-01-01","cited_by_count":23,"area":null},{"id":"2406.12158","title":"LLMs Are Prone to Fallacies in Causal Inference","created":"2024-06-18","cited_by_count":23,"area":null},{"id":"2407.10725","title":"CLAVE: An Adaptive Framework for Evaluating Values of LLM Generated Responses","created":"2024-07-15","cited_by_count":23,"area":null},{"id":"2311.07811","title":"In-context Learning Generalizes, But Not Always Robustly: The Case of Syntax","created":"2023-11-13","cited_by_count":22,"area":null},{"id":"2410.07074","title":"Let's Ask GNN: Empowering Large Language Model for Graph In-Context Learning","created":"2024-10-09","cited_by_count":21,"area":null},{"id":"2405.03146","title":"Quantifying the Capabilities of LLMs across Scale and Precision","created":"2024-05-06","cited_by_count":19,"area":null},{"id":"2410.22446","title":"Do Large Language Models Align with Core Mental Health Counseling Competencies?","created":"2024-10-29","cited_by_count":19,"area":null},{"id":"2405.13684","title":"CrossCheckGPT: Universal Hallucination Ranking for Multimodal Foundation Models","created":"2024-05-22","cited_by_count":18,"area":null},{"id":"2406.14230","title":"Raising the Bar: Investigating the Values of Large Language Models via Generative Evolving Testing","created":"2024-06-20","cited_by_count":17,"area":null},{"id":"2506.03149","title":"Causal Estimation of Tokenisation Bias","created":"2025-06-03","cited_by_count":16,"area":null},{"id":"2510.05197","title":"Efficient Prediction of Pass@k Scaling in Large Language Models","created":"2025-10-06","cited_by_count":16,"area":null},{"id":"2309.05217","title":"Quantifying and Attributing the Hallucination of Large Language Models via Association Analysis","created":"2023-09-11","cited_by_count":15,"area":null},{"id":"2405.10799","title":"Training Compute Thresholds: Features and Functions in AI Regulation","created":"2024-05-17","cited_by_count":14,"area":null},{"id":"2308.04813","title":"CLEVA: Chinese Language Models EVAluation Platform","created":"2023-08-09","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":"2601.13770","title":"Look-Ahead-Bench: a Standardized Benchmark of Look-ahead Bias in Point-in-Time LLMs for Finance","created":"2026-01-20","cited_by_count":13,"area":null},{"id":"2503.03862","title":"Not-Just-Scaling Laws: Towards a Better Understanding of the Downstream Impact of Language Model Design Decisions","created":"2025-03-05","cited_by_count":12,"area":null},{"id":"2406.17295","title":"Less can be more for predicting properties with large language models","created":"2024-06-25","cited_by_count":11,"area":null},{"id":"2502.01349","title":"Bias Beware: The Impact of Cognitive Biases on LLM-Driven Product Recommendations","created":"2025-02-03","cited_by_count":11,"area":null},{"id":"2505.14172","title":"The Strawberry Problem: Emergence of Character-level Understanding in Tokenized Language Models","created":"2025-05-20","cited_by_count":11,"area":null},{"id":"2309.16573","title":"Language Models as a Service: Overview of a New Paradigm and its Challenges","created":"2023-09-28","cited_by_count":10,"area":null},{"id":"2410.01692","title":"U-shaped and Inverted-U Scaling behind Emergent Abilities of Large Language Models","created":"2024-10-02","cited_by_count":10,"area":null},{"id":"2410.10796","title":"Context-Parametric Inversion: Why Instruction Finetuning Can Worsen Context Reliance","created":"2024-10-14","cited_by_count":10,"area":null},{"id":"2502.19190","title":"Provocations from the Humanities for Generative AI Research","created":"2025-02-26","cited_by_count":10,"area":null},{"id":"2310.05163","title":"An Investigation of LLMs' Inefficacy in Understanding Converse Relations","created":"2023-10-08","cited_by_count":9,"area":null},{"id":"2310.17551","title":"Unpacking the Ethical Value Alignment in Big Models","created":"2023-10-26","cited_by_count":9,"area":null},{"id":"2312.07779","title":"Tell, don't show: Declarative facts influence how LLMs generalize","created":"2023-12-12","cited_by_count":9,"area":null},{"id":"2402.11005","title":"A Theory of Response Sampling in LLMs: Part Descriptive and Part Prescriptive","created":"2024-02-16","cited_by_count":8,"area":null},{"id":"2408.13987","title":"Focused Large Language Models are Stable Many-Shot Learners","created":"2024-08-26","cited_by_count":8,"area":null},{"id":"2406.16069","title":"FastMem: Fast Memorization of Prompt Improves Context Awareness of Large Language Models","created":"2024-06-23","cited_by_count":7,"area":null},{"id":"2412.11979","title":"AlphaZero Neural Scaling and Zipf's Law: a Tale of Board Games and Power Laws","created":"2024-12-16","cited_by_count":7,"area":null},{"id":"2307.03762","title":"Brain in a Vat: On Missing Pieces Towards Artificial General Intelligence in Large Language Models","created":"2023-07-07","cited_by_count":6,"area":null},{"id":"2508.05464","title":"Bench-2-CoP: Can We Trust Benchmarking for EU AI Compliance?","created":"2025-08-07","cited_by_count":6,"area":null},{"id":"2402.09147","title":"Into the Unknown: Self-Learning Large Language Models","created":"2024-02-14","cited_by_count":5,"area":null},{"id":"2410.22592","title":"GRADE: Quantifying Sample Diversity in Text-to-Image Models","created":"2024-10-29","cited_by_count":5,"area":null},{"id":"2502.12552","title":"LLM Safety for Children","created":"2025-02-18","cited_by_count":5,"area":null},{"id":"2411.07990","title":"Derivational Morphology Reveals Analogical Generalization in Large Language Models","created":"2024-11-12","cited_by_count":4,"area":null},{"id":"2504.09394","title":"Evaluation Under Imperfect Benchmarks and Ratings: A Case Study in Text Simplification","created":"2025-04-13","cited_by_count":4,"area":null},{"id":"2505.10309","title":"A large-scale evaluation of commonsense knowledge in humans and large language models","created":"2025-05-15","cited_by_count":4,"area":null},{"id":"2505.13531","title":"AdAEM: An Adaptively and Automated Extensible Measurement of LLMs' Value Difference","created":"2025-05-18","cited_by_count":4,"area":null},{"id":"2506.10378","title":"Discovering Hierarchical Latent Capabilities of Language Models via Causal Representation Learning","created":"2025-06-12","cited_by_count":4,"area":null},{"id":"2507.22337","title":"A Comprehensive Taxonomy of Negation for NLP and Neural Retrievers","created":"2025-07-30","cited_by_count":4,"area":null},{"id":"2509.16332","title":"Psychometric Personality Shaping Modulates Capabilities and Safety in Language Models","created":"2025-09-19","cited_by_count":4,"area":null},{"id":"2604.00025","title":"Brevity Constraints Reverse Performance Hierarchies in Language Models","created":"2026-03-11","cited_by_count":4,"area":null},{"id":"2307.08189","title":"Mini-Giants: \"Small\" Language Models and Open Source Win-Win","created":"2023-07-17","cited_by_count":3,"area":null},{"id":"2310.11282","title":"ChapGTP, ILLC's Attempt at Raising a BabyLM: Improving Data Efficiency by Automatic Task Formation","created":"2023-10-17","cited_by_count":3,"area":null},{"id":"2311.17892","title":"A Pipeline For Discourse Circuits From CCG","created":"2023-11-29","cited_by_count":3,"area":null},{"id":"2406.02721","title":"Self-Control of LLM Behaviors by Compressing Suffix Gradient into Prefix Controller","created":"2024-06-04","cited_by_count":3,"area":null},{"id":"2410.01064","title":"Truth or Deceit? A Bayesian Decoding Game Enhances Consistency and Reliability","created":"2024-10-01","cited_by_count":3,"area":null},{"id":"2504.06486","title":"Mind the (Data) Gap: Evaluating Vision Systems in Small Data Applications","created":"2025-04-08","cited_by_count":3,"area":null},{"id":"2309.07683","title":"Assessing the nature of large language models: A caution against anthropocentrism","created":"2023-09-14","cited_by_count":2,"area":null},{"id":"2407.13164","title":"Translate-and-Revise: Boosting Large Language Models for Constrained Translation","created":"2024-07-18","cited_by_count":2,"area":null},{"id":"2504.07598","title":"On Model and Data Scaling for Skeleton-based Self-Supervised Gait Recognition","created":"2025-04-10","cited_by_count":2,"area":null},{"id":"2505.20964","title":"Semantic Communication meets System 2 ML: How Abstraction, Compositionality and Emergent Languages Shape Intelligence","created":"2025-05-27","cited_by_count":2,"area":null},{"id":"2506.00064","title":"Mis-prompt: Benchmarking Large Language Models for Proactive Error Handling","created":"2025-05-29","cited_by_count":2,"area":null},{"id":"2506.00319","title":"SkillVerse : Assessing and Enhancing LLMs with Tree Evaluation","created":"2025-05-31","cited_by_count":2,"area":null},{"id":"2509.23963","title":"Evaluating the Robustness of Chinchilla Compute-Optimal Scaling","created":"2025-09-28","cited_by_count":2,"area":null},{"id":"2510.20690","title":"Neural Diversity Regularizes Hallucinations in Language Models","created":"2025-10-23","cited_by_count":2,"area":null},{"id":"2601.19831","title":"Neural Neural Scaling Laws","created":"2026-01-27","cited_by_count":2,"area":null},{"id":"2603.26539","title":"How Open Must Language Models be to Enable Reliable Scientific Inference?","created":"2026-03-27","cited_by_count":2,"area":null},{"id":"2608.11859","title":"Small-Scale Experiments: Are We There Yet?","created":"2026-08-12","cited_by_count":2,"area":null},{"id":"2405.07436","title":"Can Language Models Explain Their Own Classification Behavior?","created":"2024-05-13","cited_by_count":1,"area":null},{"id":"2501.02842","title":"Foundations of GenIR","created":"2025-01-06","cited_by_count":1,"area":null},{"id":"2504.14596","title":"Toward the Axiomatization of Intelligence: Structure, Time, and Existence","created":"2025-04-20","cited_by_count":1,"area":null},{"id":"2508.01862","title":"Counterfactual Probing for Hallucination Detection and Mitigation in Large Language Models","created":"2025-08-03","cited_by_count":1,"area":null},{"id":"2508.08719","title":"IROTE: Human-like Traits Elicitation of Large Language Model via In-Context Self-Reflective Optimization","created":"2025-08-12","cited_by_count":1,"area":null},{"id":"2510.20387","title":"Relative-Based Scaling Law for Neural Language Models","created":"2025-10-23","cited_by_count":1,"area":null},{"id":"2512.05765","title":"AGI Requires a Coordination Layer on Top of Pattern Repositories","created":"2025-12-05","cited_by_count":1,"area":null},{"id":"2605.13825","title":"History Anchors: How Prior Behavior Steers LLM Decisions Toward Unsafe Actions","created":"2026-05-13","cited_by_count":1,"area":null},{"id":"2606.04010","title":"The Variance Brain Foundation Models Forgot: Third-Order Statistics Predict Cognition Where Billion-Parameter Models Fail","created":"2026-05-29","cited_by_count":1,"area":null},{"id":"2607.18114","title":"How Does Alignment Tuning Shape Representations of Sycophancy and Related Cue-Induced Biases in LLMs?","created":"2026-07-20","cited_by_count":1,"area":null},{"id":"2608.02639","title":"Instruction Stacking Collapse: A Benchmark and the Capability-Dependent Value of Prompt Compilation","created":"2026-07-31","cited_by_count":1,"area":null},{"id":"2401.17692","title":"Mitigating the Influence of Distractor Tasks in LMs with Prior-Aware Decoding","created":"2024-01-31","cited_by_count":0,"area":null},{"id":"2503.20088","title":"Generative Linguistics, Large Language Models, and the Social Nature of Scientific Success","created":"2025-03-25","cited_by_count":0,"area":null},{"id":"2512.03803","title":"Enhancing Instruction-Following Capabilities in Seq2Seq Models: DoLA Adaptations for T5","created":"2025-12-03","cited_by_count":0,"area":null},{"id":"2601.00850","title":"EdgeJury: Cross-Reviewed Small-Model Ensembles for Truthful Question Answering on Serverless Edge Inference","created":"2025-12-29","cited_by_count":0,"area":null},{"id":"2602.01227","title":"Supervised Fine-Tuning Needs to Unlock the Potential of Token Priority","created":"2026-02-01","cited_by_count":0,"area":null}],"next_cursor":"100"}