{"total":70,"rows":[{"id":"2303.07895","title":"The Learnability of In-Context Learning","created":"2023-03-14","cited_by_count":127,"area":null},{"id":"2401.06766","title":"Mind Your Format: Towards Consistent Evaluation of In-Context Learning Improvements","created":"2024-01-12","cited_by_count":83,"area":null},{"id":"2403.03187","title":"Reliable, Adaptable, and Attributable Language Models with Retrieval","created":"2024-03-05","cited_by_count":73,"area":"rag"},{"id":"2406.11050","title":"A Peek into Token Bias: Large Language Models Are Not Yet Genuine Reasoners","created":"2024-06-16","cited_by_count":73,"area":"lr"},{"id":"2305.14128","title":"Dr.ICL: Demonstration-Retrieved In-context Learning","created":"2023-05-23","cited_by_count":72,"area":null},{"id":"2401.11624","title":"In-context Learning with Retrieved Demonstrations for Language Models: A Survey","created":"2024-01-21","cited_by_count":70,"area":null},{"id":"2302.00618","title":"Synthetic Prompting: Generating Chain-of-Thought Demonstrations for Large Language Models","created":"2023-02-01","cited_by_count":61,"area":"lr"},{"id":"2402.18819","title":"Dual Operating Modes of In-Context Learning","created":"2024-02-29","cited_by_count":43,"area":null},{"id":"2305.15035","title":"Self-ICL: Zero-Shot In-Context Learning with Self-Generated Demonstrations","created":"2023-05-24","cited_by_count":42,"area":"synth"},{"id":"2501.02497","title":"A Survey of Test-Time Compute: From Intuitive Inference to Deliberate Reasoning","created":"2025-01-05","cited_by_count":40,"area":"lr"},{"id":"2305.05181","title":"MoT: Memory-of-Thought Enables ChatGPT to Self-Improve","created":"2023-05-09","cited_by_count":38,"area":"lr"},{"id":"2302.14691","title":"Investigating the Effectiveness of Task-Agnostic Prefix Prompt for Instruction Following","created":"2023-02-28","cited_by_count":33,"area":null},{"id":"2312.01571","title":"How to Configure Good In-Context Sequence for Visual Question Answering","created":"2023-12-04","cited_by_count":33,"area":"mllm"},{"id":"2410.05362","title":"LLMs Are In-Context Bandit Reinforcement Learners","created":"2024-10-07","cited_by_count":29,"area":null},{"id":"2304.14233","title":"Large Language Models are Strong Zero-Shot Retriever","created":"2023-04-27","cited_by_count":26,"area":null},{"id":"2402.11254","title":"C-ICL: Contrastive In-context Learning for Information Extraction","created":"2024-02-17","cited_by_count":23,"area":null},{"id":"2505.17098","title":"TACO: Enhancing Multimodal In-context Learning via Task Mapping-Guided Sequence Configuration","created":"2025-05-21","cited_by_count":23,"area":"mllm"},{"id":"2305.19783","title":"IDAS: Intent Discovery with Abstractive Summarization","created":"2023-05-31","cited_by_count":22,"area":null},{"id":"2312.15918","title":"Supervised Knowledge Makes Large Language Models Better In-context Learners","created":"2023-12-26","cited_by_count":20,"area":null},{"id":"2305.18869","title":"Dissecting Chain-of-Thought: Compositionality through In-Context Filtering and Learning","created":"2023-05-30","cited_by_count":19,"area":"lr"},{"id":"2310.12774","title":"Survival of the Most Influential Prompts: Efficient Black-Box Prompt Search via Clustering and Pruning","created":"2023-10-19","cited_by_count":17,"area":null},{"id":"2405.17264","title":"On the Noise Robustness of In-Context Learning for Text Generation","created":"2024-05-27","cited_by_count":16,"area":null},{"id":"2310.14607","title":"Confronting LLMs with Traditional ML: Rethinking the Fairness of Large Language Models in Tabular Classifications","created":"2023-10-23","cited_by_count":15,"area":"lr"},{"id":"2311.08921","title":"Self-Improving for Zero-Shot Named Entity Recognition with Large Language Models","created":"2023-11-15","cited_by_count":15,"area":"synth"},{"id":"2404.02124","title":"Exploring Automated Distractor Generation for Math Multiple-choice Questions via Large Language Models","created":"2024-04-02","cited_by_count":15,"area":null},{"id":"2305.14926","title":"Universal Self-Adaptive Prompting","created":"2023-05-24","cited_by_count":14,"area":null},{"id":"2410.05603","title":"Everything Everywhere All at Once: LLMs can In-Context Learn Multiple Tasks in Superposition","created":"2024-10-08","cited_by_count":14,"area":"mechinterp"},{"id":"2305.14877","title":"Improving Probability-based Prompt Selection Through Unified Evaluation and Analysis","created":"2023-05-24","cited_by_count":13,"area":null},{"id":"2402.12976","title":"The Impact of Demonstrations on Multilingual In-Context Learning: A Multidimensional Analysis","created":"2024-02-20","cited_by_count":13,"area":null},{"id":"2405.10548","title":"Language Models can Exploit Cross-Task In-context Learning for Data-Scarce Novel Tasks","created":"2024-05-17","cited_by_count":13,"area":null},{"id":"2402.11447","title":"In-Context Example Ordering Guided by Label Distributions","created":"2024-02-18","cited_by_count":12,"area":null},{"id":"2402.13482","title":"Retrieval-Augmented Data Augmentation for Low-Resource Domain Tasks","created":"2024-02-21","cited_by_count":12,"area":"rag"},{"id":"2309.07900","title":"Ambiguity-Aware In-Context Learning with Large Language Models","created":"2023-09-14","cited_by_count":11,"area":null},{"id":"2406.03953","title":"Tox-BART: Leveraging Toxicity Attributes for Explanation Generation of Implicit Hate Speech","created":"2024-06-06","cited_by_count":11,"area":null},{"id":"2412.07619","title":"DRUM: Learning Demonstration Retriever for Large MUlti-modal Models","created":"2024-12-10","cited_by_count":10,"area":"mllm"},{"id":"2506.02672","title":"EvaLearn: Quantifying the Learning Capability and Efficiency of LLMs via Sequential Problem Solving","created":"2025-06-03","cited_by_count":10,"area":null},{"id":"2310.08309","title":"Not All Demonstration Examples are Equally Beneficial: Reweighting Demonstration Examples for In-Context Learning","created":"2023-10-12","cited_by_count":9,"area":null},{"id":"2311.07115","title":"Gen-Z: Generative Zero-Shot Text Classification with Contextualized Label Descriptions","created":"2023-11-13","cited_by_count":9,"area":null},{"id":"2407.03672","title":"A Survey of Data Synthesis Approaches","created":"2024-07-04","cited_by_count":9,"area":"synth"},{"id":"2407.08937","title":"Self-Evolving GPT: A Lifelong Autonomous Experiential Learner","created":"2024-07-12","cited_by_count":9,"area":"synth"},{"id":"2307.02690","title":"Scaling In-Context Demonstrations with Structured Attention","created":"2023-07-05","cited_by_count":8,"area":null},{"id":"2404.07546","title":"Does In-Context Learning Really Learn? Rethinking How Large Language Models Respond and Solve Tasks via In-Context Learning","created":"2024-04-11","cited_by_count":8,"area":"lr"},{"id":"2404.12728","title":"Relevant or Random: Can LLMs Truly Perform Analogical Reasoning?","created":"2024-04-19","cited_by_count":8,"area":"lr"},{"id":"2503.04839","title":"Advancing Multimodal In-Context Learning in Large Vision-Language Models with Task-aware Demonstrations","created":"2025-03-05","cited_by_count":7,"area":"mllm"},{"id":"2309.14771","title":"Knowledgeable In-Context Tuning: Exploring and Exploiting Factual Knowledge for In-Context Learning","created":"2023-09-26","cited_by_count":6,"area":null},{"id":"2410.20215","title":"DAWN-ICL: Strategic Planning of Problem-solving Trajectories for Zero-Shot In-Context Learning","created":"2024-10-26","cited_by_count":6,"area":null},{"id":"2311.09649","title":"ICXML: An In-Context Learning Framework for Zero-Shot Extreme Multi-Label Classification","created":"2023-11-16","cited_by_count":5,"area":null},{"id":"2405.04960","title":"P-ICL: Point In-Context Learning for Named Entity Recognition with Large Language Models","created":"2024-05-08","cited_by_count":5,"area":null},{"id":"2412.07148","title":"MM-PoE: Multiple Choice Reasoning via. Process of Elimination using Multi-Modal Models","created":"2024-12-10","cited_by_count":5,"area":"lr"},{"id":"2503.21127","title":"Collaborative Evolution: Multi-Round Learning Between Large and Small Language Models for Emergent Fake News Detection","created":"2025-03-27","cited_by_count":5,"area":null},{"id":"2311.06985","title":"Large Language Models are In-context Teachers for Knowledge Reasoning","created":"2023-11-12","cited_by_count":4,"area":"lr"},{"id":"2505.16193","title":"An Empirical Study on Configuring In-Context Learning Demonstrations for Unleashing MLLMs' Sentimental Perception Capability","created":"2025-05-22","cited_by_count":4,"area":"mllm"},{"id":"2506.03100","title":"Retrieval-Augmented Generation as Noisy In-Context Learning: A Unified Theory and Risk Bounds","created":"2025-06-03","cited_by_count":4,"area":"rag"},{"id":"2512.16059","title":"ContextLeak: Auditing Leakage in Private In-Context Learning Methods","created":"2025-12-18","cited_by_count":4,"area":null},{"id":"2507.16679","title":"PICACO: Pluralistic In-Context Value Alignment of LLMs via Total Correlation Optimization","created":"2025-07-22","cited_by_count":3,"area":"alignment"},{"id":"2511.01807","title":"Plan-and-Write: Structure-Guided Length Control for LLMs without Model Retraining","created":"2025-11-03","cited_by_count":3,"area":null},{"id":"2306.02693","title":"CELDA: Leveraging Black-box Language Model as Enhanced Classifier without Labels","created":"2023-06-05","cited_by_count":2,"area":null},{"id":"2412.11923","title":"PICLe: Pseudo-Annotations for In-Context Learning in Low-Resource Named Entity Detection","created":"2024-12-16","cited_by_count":2,"area":null},{"id":"2505.07251","title":"Incomplete In-context Learning","created":"2025-05-12","cited_by_count":2,"area":"mllm"},{"id":"2506.00507","title":"Exploring In-context Example Generation for Machine Translation","created":"2025-05-31","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":"2507.09875","title":"Function Induction and Task Generalization: An Interpretability Study with Off-by-One Addition","created":"2025-07-14","cited_by_count":2,"area":null},{"id":"2408.12315","title":"Large Language Models Are Self-Taught Reasoners: Enhancing LLM Applications via Tailored Problem-Solving Demonstrations","created":"2024-08-22","cited_by_count":1,"area":"lr"},{"id":"2505.24143","title":"CrossICL: Cross-Task In-Context Learning via Unsupervised Demonstration Transfer","created":"2025-05-30","cited_by_count":1,"area":null},{"id":"2410.11693","title":"BridG MT: Enhancing LLMs' Machine Translation Capabilities with Sentence Bridging and Gradual MT","created":"2024-10-15","cited_by_count":0,"area":null},{"id":"2511.06826","title":"Beyond Plain Demos: A Demo-centric Anchoring Paradigm for In-Context Learning in Alzheimer's Disease Detection","created":"2025-11-10","cited_by_count":0,"area":null},{"id":"2604.06262","title":"From Exposure to Internalization: Dual-Stream Calibration for In-context Clinical Reasoning","created":"2026-04-07","cited_by_count":0,"area":null},{"id":"2605.23180","title":"Self-Improving In-Context Learning","created":"2026-05-22","cited_by_count":0,"area":null},{"id":"2606.29407","title":"LC-ICL: Label-Guided Contrastive In-Context Learning for Robust Information Extraction","created":"2026-06-28","cited_by_count":0,"area":null},{"id":"2609.14860","title":"One Example Is Enough to Pass Fairness Benchmarks: Rethinking Fairness Evaluation for Aligned LLMs","created":"2026-09-14","cited_by_count":0,"area":"alignment"}],"next_cursor":null}