{"total":95,"rows":[{"id":"2502.09597","title":"Do LLMs Recognize Your Preferences? Evaluating Personalized Preference Following in LLMs","created":"2025-02-13","cited_by_count":148,"area":null},{"id":"2410.02660","title":"How to Train Long-Context Language Models (Effectively)","created":"2024-10-03","cited_by_count":146,"area":null},{"id":"2410.02694","title":"HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly","created":"2024-10-03","cited_by_count":125,"area":null},{"id":"2405.16908","title":"Can Large Language Models Faithfully Express Their Intrinsic Uncertainty in Words?","created":"2024-05-27","cited_by_count":87,"area":null},{"id":"2405.09798","title":"Many-Shot In-Context Learning in Multimodal Foundation Models","created":"2024-05-16","cited_by_count":67,"area":null},{"id":"2511.02817","title":"Oolong: Evaluating Long Context Reasoning and Aggregation Capabilities","created":"2025-11-04","cited_by_count":40,"area":null},{"id":"2412.03782","title":"The broader spectrum of in-context learning","created":"2024-12-05","cited_by_count":35,"area":null},{"id":"2501.05414","title":"LongProc: Benchmarking Long-Context Language Models on Long Procedural Generation","created":"2025-01-09","cited_by_count":29,"area":null},{"id":"2510.09719","title":"ICL-Router: In-Context Learned Model Representations for LLM Routing","created":"2025-10-10","cited_by_count":28,"area":null},{"id":"2407.00402","title":"Is It Really Long Context if All You Need Is Retrieval? Towards Genuinely Difficult Long Context NLP","created":"2024-06-29","cited_by_count":27,"area":null},{"id":"2409.12181","title":"A Controlled Study on Long Context Extension and Generalization in LLMs","created":"2024-09-18","cited_by_count":26,"area":null},{"id":"2407.12108","title":"Private prediction for large-scale synthetic text generation","created":"2024-07-16","cited_by_count":24,"area":null},{"id":"2410.01359","title":"FlashMask: Efficient and Rich Mask Extension of FlashAttention","created":"2024-10-02","cited_by_count":20,"area":null},{"id":"2501.12766","title":"NExtLong: Toward Effective Long-Context Training without Long Documents","created":"2025-01-22","cited_by_count":20,"area":null},{"id":"2405.19874","title":"Is In-Context Learning Sufficient for Instruction Following in LLMs?","created":"2024-05-30","cited_by_count":19,"area":null},{"id":"2407.16695","title":"Stress-Testing Long-Context Language Models with Lifelong ICL and Task Haystack","created":"2024-07-23","cited_by_count":19,"area":null},{"id":"2502.08009","title":"The Geometry of Prompting: Unveiling Distinct Mechanisms of Task Adaptation in Language Models","created":"2025-02-11","cited_by_count":18,"area":null},{"id":"2406.11233","title":"Probing the Decision Boundaries of In-context Learning in Large Language Models","created":"2024-06-17","cited_by_count":17,"area":null},{"id":"2406.18895","title":"Can we teach language models to gloss endangered languages?","created":"2024-06-27","cited_by_count":14,"area":null},{"id":"2408.04093","title":"Tree Attention: Topology-aware Decoding for Long-Context Attention on GPU clusters","created":"2024-08-07","cited_by_count":13,"area":null},{"id":"2409.03668","title":"A Fused Large Language Model for Predicting Startup Success","created":"2024-09-05","cited_by_count":13,"area":null},{"id":"2410.05258","title":"Differential Transformer","created":"2024-10-07","cited_by_count":13,"area":null},{"id":"2410.05629","title":"Vector-ICL: In-context Learning with Continuous Vector Representations","created":"2024-10-08","cited_by_count":13,"area":null},{"id":"2505.16225","title":"MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning","created":"2025-05-22","cited_by_count":13,"area":null},{"id":"2501.04070","title":"More is not always better? Enhancing Many-Shot In-Context Learning with Differentiated and Reweighting Objectives","created":"2025-01-07","cited_by_count":12,"area":null},{"id":"2503.08640","title":"Efficient Many-Shot In-Context Learning with Dynamic Block-Sparse Attention","created":"2025-03-11","cited_by_count":12,"area":null},{"id":"2503.13299","title":"A Survey on Transformer Context Extension: Approaches and Evaluation","created":"2025-03-17","cited_by_count":11,"area":null},{"id":"2411.07130","title":"On Many-Shot In-Context Learning for Long-Context Evaluation","created":"2024-11-11","cited_by_count":10,"area":null},{"id":"2503.23306","title":"Focus Directions Make Your Language Models Pay More Attention to Relevant Contexts","created":"2025-03-30","cited_by_count":9,"area":null},{"id":"2510.16932","title":"Prompt-MII: Meta-Learning Instruction Induction for LLMs","created":"2025-10-19","cited_by_count":9,"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":"2411.02476","title":"A Comparative Analysis of Instruction Fine-Tuning LLMs for Financial Text Classification","created":"2024-11-04","cited_by_count":8,"area":null},{"id":"2412.16926","title":"Revisiting In-Context Learning with Long Context Language Models","created":"2024-12-22","cited_by_count":8,"area":null},{"id":"2508.19999","title":"Linear-Time Demonstration Selection for In-Context Learning via Gradient Estimation","created":"2025-08-27","cited_by_count":8,"area":null},{"id":"2509.13196","title":"The Few-shot Dilemma: Over-prompting Large Language Models","created":"2025-09-16","cited_by_count":8,"area":null},{"id":"2410.09343","title":"ELICIT: LLM Augmentation via External In-Context Capability","created":"2024-10-12","cited_by_count":7,"area":null},{"id":"2510.10620","title":"DCP: Addressing Input Dynamism In Long-Context Training via Dynamic Context Parallelism","created":"2025-10-12","cited_by_count":7,"area":null},{"id":"2601.15014","title":"Efficient and Minimax Optimal In-context Nonparametric Regression with Transformers","created":"2026-01-21","cited_by_count":7,"area":null},{"id":"2603.05923","title":"Learning Next Action Predictors from Human-Computer Interaction","created":"2026-03-06","cited_by_count":7,"area":null},{"id":"2406.13131","title":"When Parts Are Greater Than Sums: Individual LLM Components Can Outperform Full Models","created":"2024-06-19","cited_by_count":6,"area":null},{"id":"2407.17011","title":"Unveiling In-Context Learning: A Coordinate System to Understand Its Working Mechanism","created":"2024-07-24","cited_by_count":6,"area":null},{"id":"2407.19089","title":"Many-Shot In-Context Learning for Molecular Inverse Design","created":"2024-07-26","cited_by_count":6,"area":null},{"id":"2408.11546","title":"Memorization in In-Context Learning","created":"2024-08-21","cited_by_count":6,"area":null},{"id":"2412.13626","title":"LIFT: Improving Long Context Understanding Through Long Input Fine-Tuning","created":"2024-12-18","cited_by_count":6,"area":null},{"id":"2504.14519","title":"SlimPipe: Memory-Thrifty and Efficient Pipeline Parallelism for Long-Context LLM Training","created":"2025-04-20","cited_by_count":6,"area":null},{"id":"2410.02115","title":"L-CiteEval: Do Long-Context Models Truly Leverage Context for Responding?","created":"2024-10-03","cited_by_count":5,"area":null},{"id":"2505.21003","title":"Uncertainty Unveiled: Can Exposure to More In-context Examples Mitigate Uncertainty for Large Language Models?","created":"2025-05-27","cited_by_count":5,"area":null},{"id":"2507.04723","title":"LOOM-Scope: a comprehensive and efficient LOng-cOntext Model evaluation framework","created":"2025-07-07","cited_by_count":5,"area":null},{"id":"2510.05152","title":"A Single Character can Make or Break Your LLM Evals","created":"2025-10-02","cited_by_count":5,"area":null},{"id":"2407.05463","title":"Training Task Experts through Retrieval Based Distillation","created":"2024-07-07","cited_by_count":3,"area":null},{"id":"2410.15466","title":"Keep Guessing? When Considering Inference Scaling, Mind the Baselines","created":"2024-10-20","cited_by_count":3,"area":null},{"id":"2501.17486","title":"DINT Transformer","created":"2025-01-29","cited_by_count":3,"area":null},{"id":"2502.18791","title":"Can LLMs Help Uncover Insights about LLMs? A Large-Scale, Evolving Literature Analysis of Frontier LLMs","created":"2025-02-26","cited_by_count":3,"area":null},{"id":"2506.04579","title":"Selecting Demonstrations for Many-Shot In-Context Learning via Gradient Matching","created":"2025-06-05","cited_by_count":3,"area":null},{"id":"2507.16217","title":"Towards Compute-Optimal Many-Shot In-Context Learning","created":"2025-07-22","cited_by_count":3,"area":null},{"id":"2603.20105","title":"The $\\mathbf{Y}$-Combinator for LLMs: Solving Long-Context Rot with $\\lambda$-Calculus","created":"2026-03-20","cited_by_count":3,"area":null},{"id":"2605.13511","title":"Many-Shot CoT-ICL: Making In-Context Learning Truly Learn","created":"2026-05-13","cited_by_count":3,"area":null},{"id":"2505.20445","title":"In-context Language Learning for Endangered Languages in Speech Recognition","created":"2025-05-26","cited_by_count":2,"area":null},{"id":"2507.08021","title":"Unveiling Effective In-Context Configurations for Image Captioning: An External & Internal Analysis","created":"2025-07-08","cited_by_count":2,"area":null},{"id":"2509.20820","title":"Distilling Many-Shot In-Context Learning into a Cheat Sheet","created":"2025-09-25","cited_by_count":2,"area":null},{"id":"2511.14385","title":"Mitigating Label Length Bias in Large Language Models","created":"2025-11-18","cited_by_count":2,"area":null},{"id":"2512.19879","title":"Fine-Tuned In-Context Learners for Efficient Adaptation","created":"2025-12-22","cited_by_count":2,"area":null},{"id":"2604.10946","title":"Learning to Adapt: In-Context Learning Beyond Stationarity","created":"2026-04-13","cited_by_count":2,"area":null},{"id":"2605.05023","title":"CuBridge: An LLM-Based Framework for Understanding and Reconstructing High-Performance Attention Kernels","created":"2026-05-06","cited_by_count":2,"area":null},{"id":"2501.17900","title":"Shared DIFF Transformer","created":"2025-01-29","cited_by_count":1,"area":null},{"id":"2502.19973","title":"Can Large Language Models Unveil the Mysteries? An Exploration of Their Ability to Unlock Information in Complex Scenarios","created":"2025-02-27","cited_by_count":1,"area":null},{"id":"2506.13608","title":"Assessing the Limits of In-Context Learning beyond Functions using Partially Ordered Relation","created":"2025-06-16","cited_by_count":1,"area":null},{"id":"2507.11049","title":"Journalism-Guided Agentic In-Context Learning for News Stance Detection","created":"2025-07-15","cited_by_count":1,"area":null},{"id":"2509.00921","title":"Supervised In-Context Fine-Tuning for Generative Sequence Labeling","created":"2025-08-31","cited_by_count":1,"area":null},{"id":"2510.08372","title":"On the Relationship Between the Choice of Representation and In-Context Learning","created":"2025-10-09","cited_by_count":1,"area":null},{"id":"2510.16092","title":"Compressing Many-Shots in In-Context Learning","created":"2025-10-17","cited_by_count":1,"area":null},{"id":"2510.16809","title":"When Many-Shot Prompting Fails: An Empirical Study of LLM Code Translation","created":"2025-10-19","cited_by_count":1,"area":null},{"id":"2601.07903","title":"Enhancing Large Language Models for Time-Series Forecasting via Vector-Injected In-Context Learning","created":"2026-01-12","cited_by_count":1,"area":null},{"id":"2604.23267","title":"Fine-tuning vs. In-context Learning in Large Language Models: A Formal Language Learning Perspective","created":"2026-04-25","cited_by_count":1,"area":null},{"id":"2605.03701","title":"SERE: Structural Example Retrieval for Enhancing LLMs in Event Causality Identification","created":"2026-05-05","cited_by_count":1,"area":null},{"id":"2605.11974","title":"Towards Order Fairness: Mitigating LLMs Order Sensitivity through Dual Group Advantage Optimization","created":"2026-05-12","cited_by_count":1,"area":null},{"id":"2606.04109","title":"Discourse-Role Labels as Presentation-Time Variables for Context Use in Language Models","created":"2026-06-02","cited_by_count":1,"area":null},{"id":"2410.00344","title":"Integrating Text-to-Music Models with Language Models: Composing Long Structured Music Pieces","created":"2024-10-01","cited_by_count":0,"area":null},{"id":"2412.08955","title":"Align, Generate, Learn: A Novel Closed-Loop Framework for Cross-Lingual In-Context Learning","created":"2024-12-12","cited_by_count":0,"area":null},{"id":"2502.04580","title":"Technical Debt in In-Context Learning: Diminishing Efficiency in Long Context","created":"2025-02-07","cited_by_count":0,"area":null},{"id":"2502.05923","title":"ARISE: Iterative Rule Induction and Synthetic Data Generation for Text Classification","created":"2025-02-09","cited_by_count":0,"area":null},{"id":"2505.16333","title":"Understanding Differential Transformer Unchains Pretrained Self-Attentions","created":"2025-05-22","cited_by_count":0,"area":null},{"id":"2508.09146","title":"To Theoretically Understand Transformer-Based In-Context Learning for Optimizing CSMA","created":"2025-07-31","cited_by_count":0,"area":null},{"id":"2510.18691","title":"Investigating LLM Capabilities on Long Context Comprehension for Medical Question Answering","created":"2025-10-21","cited_by_count":0,"area":null},{"id":"2602.12123","title":"Meta-Sel: Efficient Demonstration Selection for In-Context Learning via Supervised Meta-Learning","created":"2026-02-12","cited_by_count":0,"area":null},{"id":"2604.23371","title":"When Context Sticks: Studying Interference in In-Context Learning","created":"2026-04-25","cited_by_count":0,"area":null},{"id":"2606.00472","title":"CodeCytos: AI-assisted spatial molecular imaging analysis via code-augmented agent action space","created":"2026-05-30","cited_by_count":0,"area":null},{"id":"2606.15641","title":"Distilling Examples into Task Instructions: Enhanced In-Context Learning for Real-World B2B Conversations","created":"2026-06-14","cited_by_count":0,"area":null},{"id":"2606.21890","title":"Scaling Performance and Low-Resource Annotation with Many-Shot In-Context Learning for Named Entity Recognition","created":"2026-06-20","cited_by_count":0,"area":null},{"id":"2606.29119","title":"Knowing in Advance When an Evolutionary Outer Loop Will Not Help: A Pre-Registered Cheap-Baseline Screening Rule","created":"2026-06-28","cited_by_count":0,"area":null},{"id":"2609.03213","title":"LLMs Learn Better In-Context from Rules than from Examples","created":"2026-09-02","cited_by_count":0,"area":null},{"id":"2609.29370","title":"From Policy Documents to Structured Survey Responses: Evaluating Large Language Models for Policy Monitoring","created":"2026-09-24","cited_by_count":0,"area":null},{"id":"2609.36448","title":"Theory on Attention Dynamics for Out-of-Distribution In-Context Learning","created":"2026-09-29","cited_by_count":0,"area":null},{"id":"2610.00928","title":"Efficient Task Adaptation in Large Language Models: A Survey of Weight-Based, Prompt-Based, and Embedding-Based Adaptations","created":"2026-10-01","cited_by_count":0,"area":null},{"id":"2610.04791","title":"Not All Answers Are Contextually Persuadable: Inference Dynamics in Large Language Models under Contextual Influence","created":"2026-10-03","cited_by_count":0,"area":null}],"next_cursor":null}