{"total":52,"rows":[{"id":"2311.06668","title":"In-context Vectors: Making In Context Learning More Effective and Controllable Through Latent Space Steering","created":"2023-11-11","cited_by_count":245,"area":null},{"id":"2308.07702","title":"Better Zero-Shot Reasoning with Role-Play Prompting","created":"2023-08-15","cited_by_count":223,"area":"lr"},{"id":"2309.15402","title":"Navigate through Enigmatic Labyrinth A Survey of Chain of Thought Reasoning: Advances, Frontiers and Future","created":"2023-09-27","cited_by_count":184,"area":"lr"},{"id":"2311.17076","title":"Compositional Chain-of-Thought Prompting for Large Multimodal Models","created":"2023-11-27","cited_by_count":164,"area":"lr"},{"id":"2403.16950","title":"Aligning with Human Judgement: The Role of Pairwise Preference in Large Language Model Evaluators","created":"2024-03-25","cited_by_count":149,"area":"alignment"},{"id":"2309.17249","title":"Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering","created":"2023-09-29","cited_by_count":94,"area":"lr"},{"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":"2311.05661","title":"Prompt Engineering a Prompt Engineer","created":"2023-11-09","cited_by_count":53,"area":null},{"id":"2502.13260","title":"Stepwise Perplexity-Guided Refinement for Efficient Chain-of-Thought Reasoning in Large Language Models","created":"2025-02-18","cited_by_count":51,"area":"lr"},{"id":"2406.15334","title":"Multimodal Task Vectors Enable Many-Shot Multimodal In-Context Learning","created":"2024-06-21","cited_by_count":50,"area":"mllm"},{"id":"2404.01077","title":"Efficient Prompting Methods for Large Language Models: A Survey","created":"2024-04-01","cited_by_count":47,"area":null},{"id":"2409.20441","title":"Instance-adaptive Zero-shot Chain-of-Thought Prompting","created":"2024-09-30","cited_by_count":26,"area":"lr"},{"id":"2406.11370","title":"Fairer Preferences Elicit Improved Human-Aligned Large Language Model Judgments","created":"2024-06-17","cited_by_count":25,"area":"alignment"},{"id":"2410.04521","title":"MC-CoT: A Modular Collaborative CoT Framework for Zero-shot Medical-VQA with LLM and MLLM Integration","created":"2024-10-06","cited_by_count":21,"area":"mllm"},{"id":"2502.00330","title":"From Few to Many: Self-Improving Many-Shot Reasoners Through Iterative Optimization and Generation","created":"2025-02-01","cited_by_count":21,"area":"lr"},{"id":"2504.06969","title":"Towards LLMs Robustness to Changes in Prompt Format Styles","created":"2025-04-09","cited_by_count":21,"area":null},{"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":"2402.10528","title":"Can We Verify Step by Step for Incorrect Answer Detection?","created":"2024-02-16","cited_by_count":15,"area":"lr"},{"id":"2305.14926","title":"Universal Self-Adaptive Prompting","created":"2023-05-24","cited_by_count":14,"area":null},{"id":"2403.12415","title":"VisionGPT: LLM-Assisted Real-Time Anomaly Detection for Safe Visual Navigation","created":"2024-03-19","cited_by_count":14,"area":null},{"id":"2404.09170","title":"Distilling Reasoning Ability from Large Language Models with Adaptive Thinking","created":"2024-04-14","cited_by_count":13,"area":"lr"},{"id":"2310.06692","title":"Generalizable Chain-of-Thought Prompting in Mixed-task Scenarios with Large Language Models","created":"2023-10-10","cited_by_count":11,"area":"lr"},{"id":"2410.01154","title":"Unleashing the Power of Large Language Models in Zero-shot Relation Extraction via Self-Prompting","created":"2024-10-02","cited_by_count":10,"area":null},{"id":"2310.08923","title":"Towards Informative Few-Shot Prompt with Maximum Information Gain for In-Context Learning","created":"2023-10-13","cited_by_count":9,"area":null},{"id":"2407.08937","title":"Self-Evolving GPT: A Lifelong Autonomous Experiential Learner","created":"2024-07-12","cited_by_count":9,"area":"synth"},{"id":"2505.19773","title":"What Really Matters in Many-Shot Attacks? An Empirical Study of Long-Context Vulnerabilities in LLMs","created":"2025-05-26","cited_by_count":8,"area":"safety"},{"id":"2310.13307","title":"Test-Time Self-Adaptive Small Language Models for Question Answering","created":"2023-10-20","cited_by_count":7,"area":null},{"id":"2409.15199","title":"Learning from Contrastive Prompts: Automated Optimization and Adaptation","created":"2024-09-23","cited_by_count":7,"area":null},{"id":"2403.04073","title":"Semi-Supervised Dialogue Abstractive Summarization via High-Quality Pseudolabel Selection","created":"2024-03-06","cited_by_count":5,"area":null},{"id":"2409.01552","title":"Self-Instructed Derived Prompt Generation Meets In-Context Learning: Unlocking New Potential of Black-Box LLMs","created":"2024-09-03","cited_by_count":5,"area":"synth"},{"id":"2506.14397","title":"Thunder-NUBench: A Benchmark for LLMs' Sentence-Level Negation Understanding","created":"2025-06-17","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":"2312.17601","title":"The Tyranny of Possibilities in the Design of Task-Oriented LLM Systems: A Scoping Survey","created":"2023-12-29","cited_by_count":2,"area":"agents"},{"id":"2410.15539","title":"Grammatical Error Correction for Low-Resource Languages: The Case of Zarma","created":"2024-10-20","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":"2604.02863","title":"EMS: Multi-Agent Voting via Efficient Majority-then-Stopping","created":"2026-04-03","cited_by_count":2,"area":null},{"id":"2604.09679","title":"HCP-MAD:Heterogeneous Consensus-Progressive Reasoning for Efficient Multi-Agent Debate","created":"2026-04-03","cited_by_count":2,"area":"agents"},{"id":"2605.24171","title":"PromptAudit: Auditing Prompt Sensitivity in LLM-Based Vulnerability Detection","created":"2026-05-22","cited_by_count":2,"area":null},{"id":"2402.10133","title":"Zero-Shot Reasoning: Personalized Content Generation Without the Cold Start Problem","created":"2024-02-15","cited_by_count":1,"area":"lr"},{"id":"2404.03732","title":"SHROOM-INDElab at SemEval-2024 Task 6: Zero- and Few-Shot LLM-Based Classification for Hallucination Detection","created":"2024-04-04","cited_by_count":1,"area":null},{"id":"2404.06714","title":"Llama-VITS: Enhancing TTS Synthesis with Semantic Awareness","created":"2024-04-10","cited_by_count":1,"area":null},{"id":"2406.18880","title":"SSP: Self-Supervised Prompting for Cross-Lingual Transfer to Low-Resource Languages using Large Language Models","created":"2024-06-27","cited_by_count":1,"area":null},{"id":"2410.03124","title":"In-context Demonstration Matters: On Prompt Optimization for Pseudo-Supervision Refinement","created":"2024-10-04","cited_by_count":1,"area":null},{"id":"2409.16779","title":"LLaMa-SciQ: An Educational Chatbot for Answering Science MCQ","created":"2024-09-25","cited_by_count":0,"area":"lr"},{"id":"2412.20043","title":"STAYKATE: Hybrid In-Context Example Selection Combining Representativeness Sampling and Retrieval-based Approach -- A Case Study on Science Domains","created":"2024-12-28","cited_by_count":0,"area":null},{"id":"2502.05233","title":"Efficient Knowledge Feeding to Language Models: A Novel Integrated Encoder-Decoder Architecture","created":"2025-02-07","cited_by_count":0,"area":"rag"},{"id":"2503.10662","title":"Evaluation of the Automated Labeling Method for Taxonomic Nomenclature Through Prompt-Optimized Large Language Model","created":"2025-03-08","cited_by_count":0,"area":null},{"id":"2504.10797","title":"Name of Thrones: Evaluating How LLMs Rank Student Names, Race, and Gender in Status Hierarchies","created":"2025-04-15","cited_by_count":0,"area":null},{"id":"2507.04751","title":"LLMs as Architects and Critics for Multi-Source Opinion Summarization","created":"2025-07-07","cited_by_count":0,"area":null},{"id":"2511.13007","title":"GEM: Generative Entropy-Guided Preference Modeling for Few-shot Alignment of LLMs","created":"2025-11-17","cited_by_count":0,"area":"alignment"},{"id":"2605.23180","title":"Self-Improving In-Context Learning","created":"2026-05-22","cited_by_count":0,"area":null},{"id":"2606.11640","title":"TAROT: Task-Adaptive Refinement of LLM-prior Graphs for Few-shot Tabular Learning","created":"2026-06-10","cited_by_count":0,"area":null}],"next_cursor":null}