Checklists Are Better Than Reward Models For Aligning Language Models
Fuente:
arXiv
Saved in:
| Main Authors: | Viswanathan, Vijay, Sun, Yanchao, Ma, Shuang, Kong, Xiang, Cao, Meng, Neubig, Graham, Wu, Tongshuang |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Better Synthetic Data by Retrieving and Transforming Existing Datasets
by: Gandhi, Saumya, et al.
Published: (2024)
by: Gandhi, Saumya, et al.
Published: (2024)
SELF-GUIDE: Better Task-Specific Instruction Following via Self-Synthetic Finetuning
by: Zhao, Chenyang, et al.
Published: (2024)
by: Zhao, Chenyang, et al.
Published: (2024)
Synthetic Multimodal Question Generation
by: Wu, Ian, et al.
Published: (2024)
by: Wu, Ian, et al.
Published: (2024)
ClusterFusion: Hybrid Clustering with Embedding Guidance and LLM Adaptation
by: Xu, Yiming, et al.
Published: (2025)
by: Xu, Yiming, et al.
Published: (2025)
Evaluating Language Models as Synthetic Data Generators
by: Kim, Seungone, et al.
Published: (2024)
by: Kim, Seungone, et al.
Published: (2024)
Training Task Experts through Retrieval Based Distillation
by: Ge, Jiaxin, et al.
Published: (2024)
by: Ge, Jiaxin, et al.
Published: (2024)
On the Interplay of Pre-Training, Mid-Training, and RL on Reasoning Language Models
by: Zhang, Charlie, et al.
Published: (2025)
by: Zhang, Charlie, et al.
Published: (2025)
Do LLMs exhibit human-like response biases? A case study in survey design
by: Tjuatja, Lindia, et al.
Published: (2023)
by: Tjuatja, Lindia, et al.
Published: (2023)
BehaviorBox: Automated Discovery of Fine-Grained Performance Differences Between Language Models
by: Tjuatja, Lindia, et al.
Published: (2025)
by: Tjuatja, Lindia, et al.
Published: (2025)
RefineBench: Evaluating Refinement Capability of Language Models via Checklists
by: Lee, Young-Jun, et al.
Published: (2025)
by: Lee, Young-Jun, et al.
Published: (2025)
An Incomplete Loop: Instruction Inference, Instruction Following, and In-context Learning in Language Models
by: Liu, Emmy, et al.
Published: (2024)
by: Liu, Emmy, et al.
Published: (2024)
Asking What Matters: Reward-Driven Clarification for Software Engineering Tasks
by: Vijayvargiya, Sanidhya, et al.
Published: (2026)
by: Vijayvargiya, Sanidhya, et al.
Published: (2026)
Instruction-tuned Language Models are Better Knowledge Learners
by: Jiang, Zhengbao, et al.
Published: (2024)
by: Jiang, Zhengbao, et al.
Published: (2024)
The Accuracy Paradox in RLHF: When Better Reward Models Don't Yield Better Language Models
by: Chen, Yanjun, et al.
Published: (2024)
by: Chen, Yanjun, et al.
Published: (2024)
Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment
by: Zhang, Jiazheng, et al.
Published: (2025)
by: Zhang, Jiazheng, et al.
Published: (2025)
Better Instruction-Following Through Minimum Bayes Risk
by: Wu, Ian, et al.
Published: (2024)
by: Wu, Ian, et al.
Published: (2024)
Shallow Preference Signals: Large Language Model Aligns Even Better with Truncated Data?
by: Qi, Xuan, et al.
Published: (2025)
by: Qi, Xuan, et al.
Published: (2025)
Pre-Trained Language Models Represent Some Geographic Populations Better Than Others
by: Dunn, Jonathan, et al.
Published: (2024)
by: Dunn, Jonathan, et al.
Published: (2024)
Text2Reward: Reward Shaping with Language Models for Reinforcement Learning
by: Xie, Tianbao, et al.
Published: (2023)
by: Xie, Tianbao, et al.
Published: (2023)
Go-Browse: Training Web Agents with Structured Exploration
by: Gandhi, Apurva, et al.
Published: (2025)
by: Gandhi, Apurva, et al.
Published: (2025)
Prior Constraints-based Reward Model Training for Aligning Large Language Models
by: Zhou, Hang, et al.
Published: (2024)
by: Zhou, Hang, et al.
Published: (2024)
Repetition Improves Language Model Embeddings
by: Springer, Jacob Mitchell, et al.
Published: (2024)
by: Springer, Jacob Mitchell, et al.
Published: (2024)
Sentence-level Reward Model can Generalize Better for Aligning LLM from Human Preference
by: Qiu, Wenjie, et al.
Published: (2025)
by: Qiu, Wenjie, et al.
Published: (2025)
HSCR: Hierarchical Self-Contrastive Rewarding for Aligning Medical Vision Language Models
by: Jiang, Songtao, et al.
Published: (2025)
by: Jiang, Songtao, et al.
Published: (2025)
Can Large Language Models be Trusted for Evaluation? Scalable Meta-Evaluation of LLMs as Evaluators via Agent Debate
by: Chern, Steffi, et al.
Published: (2024)
by: Chern, Steffi, et al.
Published: (2024)
Better Language Model-Based Judging Reward Modeling through Scaling Comprehension Boundaries
by: Ning, Meiling, et al.
Published: (2025)
by: Ning, Meiling, et al.
Published: (2025)
VisualPuzzles: Decoupling Multimodal Reasoning Evaluation from Domain Knowledge
by: Song, Yueqi, et al.
Published: (2025)
by: Song, Yueqi, et al.
Published: (2025)
What do Language Models Learn and When? The Implicit Curriculum Hypothesis
by: Liu, Emmy, et al.
Published: (2026)
by: Liu, Emmy, et al.
Published: (2026)
Personalized RewardBench: Evaluating Reward Models with Human Aligned Personalization
by: Ma, Qiyao, et al.
Published: (2026)
by: Ma, Qiyao, et al.
Published: (2026)
Benchmarking Failures in Tool-Augmented Language Models
by: Treviño, Eduardo, et al.
Published: (2025)
by: Treviño, Eduardo, et al.
Published: (2025)
Direct Large Language Model Alignment Through Self-Rewarding Contrastive Prompt Distillation
by: Liu, Aiwei, et al.
Published: (2024)
by: Liu, Aiwei, et al.
Published: (2024)
Aligning Language Models Using Follow-up Likelihood as Reward Signal
by: Zhang, Chen, et al.
Published: (2024)
by: Zhang, Chen, et al.
Published: (2024)
What Are Tools Anyway? A Survey from the Language Model Perspective
by: Wang, Zhiruo, et al.
Published: (2024)
by: Wang, Zhiruo, et al.
Published: (2024)
CMULAB: An Open-Source Framework for Training and Deployment of Natural Language Processing Models
by: Sheikh, Zaid, et al.
Published: (2024)
by: Sheikh, Zaid, et al.
Published: (2024)
Overtrained Language Models Are Harder to Fine-Tune
by: Springer, Jacob Mitchell, et al.
Published: (2025)
by: Springer, Jacob Mitchell, et al.
Published: (2025)
KARMA: Karma-Aligned Reward Model Adaptation
by: Scott, Jared, et al.
Published: (2026)
by: Scott, Jared, et al.
Published: (2026)
Fine-grained Hallucination Detection and Editing for Language Models
by: Mishra, Abhika, et al.
Published: (2024)
by: Mishra, Abhika, et al.
Published: (2024)
Language Modeling with Editable External Knowledge
by: Li, Belinda Z., et al.
Published: (2024)
by: Li, Belinda Z., et al.
Published: (2024)
Not-Just-Scaling Laws: Towards a Better Understanding of the Downstream Impact of Language Model Design Decisions
by: Liu, Emmy, et al.
Published: (2025)
by: Liu, Emmy, et al.
Published: (2025)
Effective Strategies for Asynchronous Software Engineering Agents
by: Geng, Jiayi, et al.
Published: (2026)
by: Geng, Jiayi, et al.
Published: (2026)
Similar Items
-
Better Synthetic Data by Retrieving and Transforming Existing Datasets
by: Gandhi, Saumya, et al.
Published: (2024) -
SELF-GUIDE: Better Task-Specific Instruction Following via Self-Synthetic Finetuning
by: Zhao, Chenyang, et al.
Published: (2024) -
Synthetic Multimodal Question Generation
by: Wu, Ian, et al.
Published: (2024) -
ClusterFusion: Hybrid Clustering with Embedding Guidance and LLM Adaptation
by: Xu, Yiming, et al.
Published: (2025) -
Evaluating Language Models as Synthetic Data Generators
by: Kim, Seungone, et al.
Published: (2024)