{"total":25,"rows":[{"id":"2312.16682","title":"Some things are more CRINGE than others: Iterative Preference Optimization with the Pairwise Cringe Loss","created":"2023-12-27","cited_by_count":108,"area":"alignment"},{"id":"2405.17977","title":"Aligning to Thousands of Preferences via System Message Generalization","created":"2024-05-28","cited_by_count":84,"area":"alignment"},{"id":"2310.09520","title":"Reward-Augmented Decoding: Efficient Controlled Text Generation With a Unidirectional Reward Model","created":"2023-10-14","cited_by_count":79,"area":"alignment"},{"id":"2405.13967","title":"Model Editing as a Robust and Denoised variant of DPO: A Case Study on Toxicity","created":"2024-05-22","cited_by_count":35,"area":"alignment"},{"id":"2401.07382","title":"Beyond Sparse Rewards: Enhancing Reinforcement Learning with Language Model Critique in Text Generation","created":"2024-01-14","cited_by_count":22,"area":"alignment"},{"id":"2505.10717","title":"A Modular Approach for Clinical SLMs Driven by Synthetic Data with Pre-Instruction Tuning, Model Merging, and Clinical-Tasks Alignment","created":"2025-05-15","cited_by_count":20,"area":"alignment"},{"id":"2202.09662","title":"Reward Modeling for Mitigating Toxicity in Transformer-based Language Models","created":"2022-02-19","cited_by_count":18,"area":"alignment"},{"id":"2410.03769","title":"SciSafeEval: A Comprehensive Benchmark for Safety Alignment of Large Language Models in Scientific Tasks","created":"2024-10-02","cited_by_count":18,"area":"alignment"},{"id":"2503.01048","title":"Personalize Your LLM: Fake it then Align it","created":"2025-03-02","cited_by_count":15,"area":"alignment"},{"id":"2603.04069","title":"Monitoring Emergent Reward Hacking During Generation via Internal Activations","created":"2026-03-04","cited_by_count":14,"area":"alignment"},{"id":"2510.01243","title":"Detoxifying Large Language Models via Autoregressive Reward Guided Representation Editing","created":"2025-09-24","cited_by_count":10,"area":"alignment"},{"id":"2410.03818","title":"Large Language Models can be Strong Self-Detoxifiers","created":"2024-10-04","cited_by_count":7,"area":"alignment"},{"id":"2411.10912","title":"SPICA: Retrieving Scenarios for Pluralistic In-Context Alignment","created":"2024-11-16","cited_by_count":6,"area":"alignment"},{"id":"2407.16970","title":"Towards Aligning Language Models with Textual Feedback","created":"2024-07-24","cited_by_count":5,"area":"alignment"},{"id":"2410.00409","title":"AlignSum: Data Pyramid Hierarchical Fine-tuning for Aligning with Human Summarization Preference","created":"2024-10-01","cited_by_count":4,"area":"alignment"},{"id":"2510.14702","title":"Cognitive-Aligned Spatio-Temporal Large Language Models For Next Point-of-Interest Prediction","created":"2025-10-16","cited_by_count":2,"area":"alignment"},{"id":"2601.05882","title":"An Empirical Study on Preference Tuning Generalization and Diversity Under Domain Shift","created":"2026-01-09","cited_by_count":2,"area":"alignment"},{"id":"2411.10545","title":"Efficient Alignment of Large Language Models via Data Sampling","created":"2024-11-15","cited_by_count":1,"area":"alignment"},{"id":"2510.10077","title":"A-IPO: Adaptive Intent-driven Preference Optimization","created":"2025-10-11","cited_by_count":1,"area":"alignment"},{"id":"2510.17652","title":"Qomhra: A Bilingual Irish and English Large Language Model","created":"2025-10-20","cited_by_count":1,"area":"alignment"},{"id":"2511.21101","title":"Mortgage Language Model: Domain-Adaptive Pretraining with Residual Instruction, Alignment Tuning, and Task-Specific Routing","created":"2025-11-26","cited_by_count":1,"area":"alignment"},{"id":"2512.08777","title":"Fluent Alignment with Disfluent Judges: Post-training for Lower-resource Languages","created":"2025-12-09","cited_by_count":0,"area":"alignment"},{"id":"2601.09718","title":"StatLLaMA: Multi-Stage training for domain-optimized statistical large language models","created":"2025-12-26","cited_by_count":0,"area":"alignment"},{"id":"2604.16378","title":"Reciprocal Co-Training (RCT): Coupling Gradient-Based and Non-Differentiable Models via Reinforcement Learning","created":"2026-03-24","cited_by_count":0,"area":"alignment"},{"id":"2609.35201","title":"From Normative Frameworks to Alignment Data: Constructing and Evaluating SFT and Preference Data","created":"2026-09-28","cited_by_count":0,"area":"alignment"}],"next_cursor":null}