{"total":102,"rows":[{"id":"2103.00020","title":"Learning Transferable Visual Models From Natural Language Supervision","created":"2021-02-26","cited_by_count":33744,"area":"wm"},{"id":"2203.02155","title":"Training language models to follow instructions with human feedback","created":"2022-03-04","cited_by_count":15971,"area":"alignment"},{"id":"2009.01325","title":"Learning to summarize from human feedback","created":"2020-09-02","cited_by_count":2588,"area":"alignment"},{"id":"1909.08593","title":"Fine-Tuning Language Models from Human Preferences","created":"2019-09-18","cited_by_count":2150,"area":"alignment"},{"id":"2202.03629","title":"Survey of Hallucination in Natural Language Generation","created":"2022-02-08","cited_by_count":2075,"area":null},{"id":"2305.14387","title":"AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback","created":"2023-05-22","cited_by_count":748,"area":"alignment"},{"id":"2305.02301","title":"Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes","created":"2023-05-03","cited_by_count":737,"area":null},{"id":"2104.14337","title":"Dynabench: Rethinking Benchmarking in NLP","created":"2021-04-07","cited_by_count":459,"area":null},{"id":"2306.01693","title":"Fine-Grained Human Feedback Gives Better Rewards for Language Model Training","created":"2023-06-02","cited_by_count":401,"area":"alignment"},{"id":"2109.10862","title":"Recursively Summarizing Books with Human Feedback","created":"2021-09-22","cited_by_count":290,"area":null},{"id":"1907.00456","title":"Way Off-Policy Batch Deep Reinforcement Learning of Implicit Human Preferences in Dialog","created":"2019-06-30","cited_by_count":284,"area":"offlinerl"},{"id":"2108.00941","title":"A Survey of Human-in-the-loop for Machine Learning","created":"2021-08-02","cited_by_count":215,"area":null},{"id":"2212.09611","title":"Optimizing Prompts for Text-to-Image Generation","created":"2022-12-19","cited_by_count":207,"area":null},{"id":"2208.03188","title":"BlenderBot 3: a deployed conversational agent that continually learns to responsibly engage","created":"2022-08-05","cited_by_count":198,"area":null},{"id":"2302.02676","title":"Chain of Hindsight Aligns Language Models with Feedback","created":"2023-02-06","cited_by_count":148,"area":"alignment"},{"id":"2105.04387","title":"Recent Advances in Deep Learning Based Dialogue Systems: A Systematic Survey","created":"2021-05-10","cited_by_count":130,"area":null},{"id":"2303.16755","title":"Training Language Models with Language Feedback at Scale","created":"2023-03-28","cited_by_count":128,"area":"alignment"},{"id":"2010.05848","title":"Human-centric Dialog Training via Offline Reinforcement Learning","created":"2020-10-12","cited_by_count":93,"area":"offlinerl"},{"id":"2404.08555","title":"RLHF Deciphered: A Critical Analysis of Reinforcement Learning from Human Feedback for LLMs","created":"2024-04-12","cited_by_count":90,"area":"alignment"},{"id":"2506.03106","title":"Critique-GRPO: Advancing LLM Reasoning with Natural Language and Numerical Feedback","created":"2025-06-03","cited_by_count":90,"area":"lr"},{"id":"2303.05453","title":"Personalisation within bounds: A risk taxonomy and policy framework for the alignment of large language models with personalised feedback","created":"2023-03-09","cited_by_count":87,"area":"alignment"},{"id":"2107.03451","title":"Anticipating Safety Issues in E2E Conversational AI: Framework and Tooling","created":"2021-07-07","cited_by_count":78,"area":null},{"id":"2407.01599","title":"JailbreakZoo: Survey, Landscapes, and Horizons in Jailbreaking Large Language and Vision-Language Models","created":"2024-06-26","cited_by_count":70,"area":"mllm"},{"id":"2404.15269","title":"Aligning LLM Agents by Learning Latent Preference from User Edits","created":"2024-04-23","cited_by_count":69,"area":"agents"},{"id":"2109.05794","title":"Building and Evaluating Open-Domain Dialogue Corpora with Clarifying Questions","created":"2021-09-13","cited_by_count":63,"area":null},{"id":"2305.00955","title":"Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language Generation","created":"2023-05-01","cited_by_count":55,"area":"alignment"},{"id":"2310.07629","title":"The Past, Present and Better Future of Feedback Learning in Large Language Models for Subjective Human Preferences and Values","created":"2023-10-11","cited_by_count":54,"area":"alignment"},{"id":"2204.14146","title":"Training Language Models with Language Feedback","created":"2022-04-29","cited_by_count":49,"area":"alignment"},{"id":"2402.04616","title":"Beyond Answers: Transferring Reasoning Capabilities to Smaller LLMs Using Multi-Teacher Knowledge Distillation","created":"2024-02-07","cited_by_count":47,"area":"lr"},{"id":"2106.02192","title":"Grounding 'Grounding' in NLP","created":"2021-06-04","cited_by_count":44,"area":null},{"id":"2103.04044","title":"Putting Humans in the Natural Language Processing Loop: A Survey","created":"2021-03-06","cited_by_count":40,"area":null},{"id":"2211.05826","title":"The CRINGE Loss: Learning what language not to model","created":"2022-11-10","cited_by_count":39,"area":null},{"id":"2110.07518","title":"SaFeRDialogues: Taking Feedback Gracefully after Conversational Safety Failures","created":"2021-10-14","cited_by_count":37,"area":null},{"id":"2208.03270","title":"Learning New Skills after Deployment: Improving open-domain internet-driven dialogue with human feedback","created":"2022-08-05","cited_by_count":36,"area":"alignment"},{"id":"2306.00398","title":"Preference-grounded Token-level Guidance for Language Model Fine-tuning","created":"2023-06-01","cited_by_count":31,"area":"alignment"},{"id":"2204.03025","title":"Using Interactive Feedback to Improve the Accuracy and Explainability of Question Answering Systems Post-Deployment","created":"2022-04-06","cited_by_count":25,"area":null},{"id":"2403.19443","title":"Mixed Preference Optimization: Reinforcement Learning with Data Selection and Better Reference Model","created":"2024-03-28","cited_by_count":25,"area":"alignment"},{"id":"2406.11191","title":"A Survey on Human Preference Learning for Large Language Models","created":"2024-06-17","cited_by_count":24,"area":"alignment"},{"id":"2210.15893","title":"When Life Gives You Lemons, Make Cherryade: Converting Feedback from Bad Responses into Good Labels","created":"2022-10-28","cited_by_count":20,"area":"alignment"},{"id":"2305.08195","title":"Learning to Simulate Natural Language Feedback for Interactive Semantic Parsing","created":"2023-05-14","cited_by_count":19,"area":null},{"id":"2309.08008","title":"An Empirical Evaluation of Prompting Strategies for Large Language Models in Zero-Shot Clinical Natural Language Processing","created":"2023-09-14","cited_by_count":19,"area":null},{"id":"2402.10893","title":"RLVF: Learning from Verbal Feedback without Overgeneralization","created":"2024-02-16","cited_by_count":19,"area":"alignment"},{"id":"2507.23158","title":"User Feedback in Human-LLM Dialogues: A Lens to Understand Users But Noisy as a Learning Signal","created":"2025-07-30","cited_by_count":19,"area":null},{"id":"2510.06672","title":"XRPO: Pushing the limits of GRPO with Targeted Exploration and Exploitation","created":"2025-10-08","cited_by_count":18,"area":"lr"},{"id":"2206.00059","title":"A Mixture-of-Expert Approach to RL-based Dialogue Management","created":"2022-05-31","cited_by_count":16,"area":"moe"},{"id":"2307.14117","title":"Leveraging Implicit Feedback from Deployment Data in Dialogue","created":"2023-07-26","cited_by_count":14,"area":null},{"id":"2401.04883","title":"Multi-User Chat Assistant (MUCA): a Framework Using LLMs to Facilitate Group Conversations","created":"2024-01-10","cited_by_count":14,"area":null},{"id":"2407.10944","title":"Naturally Occurring Feedback is Common, Extractable and Useful","created":"2024-07-15","cited_by_count":14,"area":"alignment"},{"id":"2509.25137","title":"The Era of Real-World Human Interaction: RL from User Conversations","created":"2025-09-29","cited_by_count":13,"area":null},{"id":"2011.02511","title":"Offline Reinforcement Learning from Human Feedback in Real-World Sequence-to-Sequence Tasks","created":"2020-11-04","cited_by_count":12,"area":"alignment"},{"id":"2501.02790","title":"Segmenting Text and Learning Their Rewards for Improved RLHF in Language Model","created":"2025-01-06","cited_by_count":12,"area":"alignment"},{"id":"2106.10901","title":"Software-Based Dialogue Systems: Survey, Taxonomy and Challenges","created":"2021-06-21","cited_by_count":11,"area":null},{"id":"2208.03295","title":"Learning from data in the mixed adversarial non-adversarial case: Finding the helpers and ignoring the trolls","created":"2022-08-05","cited_by_count":11,"area":null},{"id":"2208.14165","title":"Towards Boosting the Open-Domain Chatbot with Human Feedback","created":"2022-08-30","cited_by_count":11,"area":"alignment"},{"id":"2212.10755","title":"JASMINE: Arabic GPT Models for Few-Shot Learning","created":"2022-12-21","cited_by_count":11,"area":null},{"id":"2306.04707","title":"Improving Open Language Models by Learning from Organic Interactions","created":"2023-06-07","cited_by_count":10,"area":null},{"id":"2408.16961","title":"The Future of Open Human Feedback","created":"2024-08-15","cited_by_count":10,"area":"alignment"},{"id":"2411.09947","title":"LoRA-LiteE: A Computationally Efficient Framework for Chatbot Preference-Tuning","created":"2024-11-15","cited_by_count":10,"area":"alignment"},{"id":"2101.06984","title":"Studying Catastrophic Forgetting in Neural Ranking Models","created":"2021-01-18","cited_by_count":9,"area":null},{"id":"2106.00162","title":"HERALD: An Annotation Efficient Method to Detect User Disengagement in Social Conversations","created":"2021-06-01","cited_by_count":9,"area":null},{"id":"2201.06849","title":"Toward Self-learning End-to-End Task-Oriented Dialog Systems","created":"2022-01-18","cited_by_count":9,"area":null},{"id":"2307.00279","title":"Let Me Teach You: Pedagogical Foundations of Feedback for Language Models","created":"2023-07-01","cited_by_count":9,"area":"alignment"},{"id":"2212.09750","title":"Human-in-the-loop Abstractive Dialogue Summarization","created":"2022-12-19","cited_by_count":8,"area":null},{"id":"2402.07742","title":"Asking Multimodal Clarifying Questions in Mixed-Initiative Conversational Search","created":"2024-02-12","cited_by_count":8,"area":null},{"id":"2408.08291","title":"The ShareLM Collection and Plugin: Contributing Human-Model Chats for the Benefit of the Community","created":"2024-08-15","cited_by_count":8,"area":null},{"id":"2506.06518","title":"A Systematic Review of Poisoning Attacks Against Large Language Models","created":"2025-06-06","cited_by_count":8,"area":null},{"id":"2310.15758","title":"Learning From Free-Text Human Feedback -- Collect New Datasets Or Extend Existing Ones?","created":"2023-10-24","cited_by_count":7,"area":"alignment"},{"id":"2211.05750","title":"Nano: Nested Human-in-the-Loop Reward Learning for Few-shot Language Model Control","created":"2022-11-10","cited_by_count":6,"area":"alignment"},{"id":"2305.12594","title":"Modeling User Satisfaction Dynamics in Dialogue via Hawkes Process","created":"2023-05-21","cited_by_count":6,"area":null},{"id":"2410.13852","title":"Retrospective Learning from Interactions","created":"2024-10-17","cited_by_count":6,"area":null},{"id":"2502.07237","title":"DrugImproverGPT: A Large Language Model for Drug Optimization with Fine-Tuning via Structured Policy Optimization","created":"2025-02-11","cited_by_count":6,"area":null},{"id":"2109.12451","title":"Deciding Whether to Ask Clarifying Questions in Large-Scale Spoken Language Understanding","created":"2021-09-25","cited_by_count":5,"area":null},{"id":"2502.03397","title":"SPRI: Aligning Large Language Models with Context-Situated Principles","created":"2025-02-05","cited_by_count":5,"area":"alignment"},{"id":"2510.02341","title":"DRIFT: Learning from Abundant User Dissatisfaction in Real-World Preference Learning","created":"2025-09-27","cited_by_count":5,"area":"alignment"},{"id":"2306.13588","title":"System-Level Natural Language Feedback","created":"2023-06-23","cited_by_count":4,"area":"alignment"},{"id":"2407.03956","title":"Solving Zebra Puzzles Using Constraint-Guided Multi-Agent Systems","created":"2024-07-04","cited_by_count":4,"area":"lr"},{"id":"2508.03296","title":"Towards Trustworthy Multimodal Moderation via Policy-Aligned Reasoning and Hierarchical Labeling","created":"2025-08-05","cited_by_count":4,"area":null},{"id":"2601.22900","title":"MulFeRL: Enhancing Reinforcement Learning with Verbal Feedback in a Multi-turn Loop","created":"2026-01-30","cited_by_count":4,"area":"lr"},{"id":"2106.11345","title":"Cogment: Open Source Framework For Distributed Multi-actor Training, Deployment & Operations","created":"2021-06-21","cited_by_count":3,"area":null},{"id":"2310.15594","title":"Retrieval-based Knowledge Transfer: An Effective Approach for Extreme Large Language Model Compression","created":"2023-10-24","cited_by_count":3,"area":null},{"id":"2401.09248","title":"Learning from Implicit User Feedback, Emotions and Demographic Information in Task-Oriented and Document-Grounded Dialogues","created":"2024-01-17","cited_by_count":3,"area":null},{"id":"2502.11442","title":"Multi-Turn Multi-Modal Question Clarification for Enhanced Conversational Understanding","created":"2025-02-17","cited_by_count":3,"area":null},{"id":"2511.09002","title":"Convergence and Stability Analysis of Self-Consuming Generative Models with Heterogeneous Human Curation","created":"2025-11-12","cited_by_count":3,"area":null},{"id":"2102.13589","title":"Evaluate On-the-job Learning Dialogue Systems and a Case Study for Natural Language Understanding","created":"2021-02-26","cited_by_count":2,"area":null},{"id":"2209.07873","title":"Adaptive Natural Language Generation for Task-oriented Dialogue via Reinforcement Learning","created":"2022-09-16","cited_by_count":2,"area":null},{"id":"2307.05399","title":"Domain-Agnostic Neural Architecture for Class Incremental Continual Learning in Document Processing Platform","created":"2023-07-11","cited_by_count":2,"area":null},{"id":"2110.12412","title":"Improved Goal Oriented Dialogue via Utterance Generation and Look Ahead","created":"2021-10-24","cited_by_count":1,"area":null},{"id":"2204.08687","title":"Many Episode Learning in a Modular Embodied Agent via End-to-End Interaction","created":"2022-04-19","cited_by_count":1,"area":null},{"id":"2309.10413","title":"PICK: Polished & Informed Candidate Scoring for Knowledge-Grounded Dialogue Systems","created":"2023-09-19","cited_by_count":1,"area":null},{"id":"2506.23273","title":"FinStat2SQL: A Text2SQL Pipeline for Financial Statement Analysis","created":"2025-06-29","cited_by_count":1,"area":null},{"id":"2603.01973","title":"CharacterFlywheel: Scaling Iterative Improvement of Engaging and Steerable LLMs in Production","created":"2026-03-02","cited_by_count":1,"area":null},{"id":"2110.07337","title":"Topic-time Heatmaps for Human-in-the-loop Topic Detection and Tracking","created":"2021-10-12","cited_by_count":0,"area":null},{"id":"2110.13213","title":"Findings from Experiments of On-line Joint Reinforcement Learning of Semantic Parser and Dialogue Manager with real Users","created":"2021-10-25","cited_by_count":0,"area":null},{"id":"2305.08818","title":"Sentence Level Curriculum Learning for Improved Neural Conversational Models","created":"2023-05-15","cited_by_count":0,"area":null},{"id":"2407.20197","title":"Learning Random Numbers to Realize Appendable Memory System for Artificial Intelligence to Acquire New Knowledge after Deployment","created":"2024-07-29","cited_by_count":0,"area":null},{"id":"2410.07094","title":"An Approach for Auto Generation of Labeling Functions for Software Engineering Chatbots","created":"2024-10-09","cited_by_count":0,"area":null},{"id":"2509.01885","title":"Extracting OPQRST in Electronic Health Records using Large Language Models with Reasoning","created":"2025-09-02","cited_by_count":0,"area":"lr"},{"id":"2510.03696","title":"Mind the Goal: Data-Efficient Goal-Oriented Evaluation of Conversational Agents and Chatbots using Teacher Models","created":"2025-10-04","cited_by_count":0,"area":"agents"},{"id":"2603.04822","title":"VISA: Value Injection via Shielded Adaptation for Personalized LLM Alignment","created":"2026-03-05","cited_by_count":0,"area":"alignment"},{"id":"2605.25204","title":"Clarification Is Not Enough: Post-Clarification Answering Remains the Bottleneck in Multi-Turn QA","created":"2026-05-24","cited_by_count":0,"area":null}],"next_cursor":"100"}