Cover Image

Peering Through Preferences: Unraveling Feedback Acquisition for Aligning Large Language Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Bansal, Hritik, Dang, John, Grover, Aditya
Format:	Preprint
Published:	2023
Subjects:	Machine Learning Artificial Intelligence Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Comparing Bad Apples to Good Oranges: Aligning Large Language Models via Joint Preference Optimization
by: Bansal, Hritik, et al.
Published: (2024)

Group Preference Optimization: Few-Shot Alignment of Large Language Models
by: Zhao, Siyan, et al.
Published: (2023)

When To Solve, When To Verify: Compute-Optimal Problem Solving and Generative Verification for LLM Reasoning
by: Singhi, Nishad, et al.
Published: (2025)

Peeking Behind Closed Doors: Risks of LLM Evaluation by Private Data Curators
by: Bansal, Hritik, et al.
Published: (2025)

Probing the Decision Boundaries of In-context Learning in Large Language Models
by: Zhao, Siyan, et al.
Published: (2024)

Online Intrinsic Rewards for Decision Making Agents from Large Language Model Feedback
by: Zheng, Qinqing, et al.
Published: (2024)

TALC: Time-Aligned Captions for Multi-Scene Text-to-Video Generation
by: Bansal, Hritik, et al.
Published: (2024)

A Critical Evaluation of AI Feedback for Aligning Large Language Models
by: Sharma, Archit, et al.
Published: (2024)

Prepacking: A Simple Method for Fast Prefilling and Increased Throughput in Large Language Models
by: Zhao, Siyan, et al.
Published: (2024)

Aligning with Human Judgement: The Role of Pairwise Preference in Large Language Model Evaluators
by: Liu, Yinhong, et al.
Published: (2024)

Towards Aligning Language Models with Textual Feedback
by: Lloret, Saüc Abadal, et al.
Published: (2024)

SUPERNOVA: Eliciting General Reasoning in LLMs with Reinforcement Learning on Natural Instructions
by: Suvarna, Ashima, et al.
Published: (2026)

Sequence-level Large Language Model Training with Contrastive Preference Optimization
by: Feng, Zhili, et al.
Published: (2025)

LifeAlign: Lifelong Alignment for Large Language Models with Memory-Augmented Focalized Preference Optimization
by: Li, Junsong, et al.
Published: (2025)

Remember This Event That Year? Assessing Temporal Information and Reasoning in Large Language Models
by: Beniwal, Himanshu, et al.
Published: (2024)

Fairer Preferences Elicit Improved Human-Aligned Large Language Model Judgments
by: Zhou, Han, et al.
Published: (2024)

CHAI for LLMs: Improving Code-Mixed Translation in Large Language Models through Reinforcement Learning with AI Feedback
by: Zhang, Wenbo, et al.
Published: (2024)

Align to Structure: Aligning Large Language Models with Structural Information
by: Kim, Zae Myung, et al.
Published: (2025)

Enabling Autoregressive Models to Fill In Masked Tokens
by: Israel, Daniel, et al.
Published: (2025)

Reasoning Elicitation in Language Models via Counterfactual Feedback
by: Hüyük, Alihan, et al.
Published: (2024)

Active Preference Learning for Large Language Models
by: Muldrew, William, et al.
Published: (2024)

GUNDAM: Aligning Large Language Models with Graph Understanding
by: Ouyang, Sheng, et al.
Published: (2024)

Aligning Large Language Models by On-Policy Self-Judgment
by: Lee, Sangkyu, et al.
Published: (2024)

RLHF Can Speak Many Languages: Unlocking Multilingual Preference Optimization for LLMs
by: Dang, John, et al.
Published: (2024)

Unraveling the cognitive patterns of Large Language Models through module communities
by: Bhandari, Kushal Raj, et al.
Published: (2025)

ROPO: Robust Preference Optimization for Large Language Models
by: Liang, Xize, et al.
Published: (2024)

Accelerated Preference Optimization for Large Language Model Alignment
by: He, Jiafan, et al.
Published: (2024)

AlignBench: Benchmarking Chinese Alignment of Large Language Models
by: Liu, Xiao, et al.
Published: (2023)

Aligning Large Language Models via Fine-grained Supervision
by: Xu, Dehong, et al.
Published: (2024)

AMPO: Active Multi-Preference Optimization for Self-play Preference Selection
by: Gupta, Taneesh, et al.
Published: (2025)

From Noisy Traces to Stable Gradients: Bias-Variance Optimized Preference Optimization for Aligning Large Reasoning Models
by: Zhu, Mingkang, et al.
Published: (2025)

Is Active Persona Inference Necessary for Aligning Small Models to Personal Preferences?
by: Tang, Zilu, et al.
Published: (2025)

Self-Rewarding PPO: Aligning Large Language Models with Demonstrations Only
by: Zhang, Qingru, et al.
Published: (2025)

Alignment Studio: Aligning Large Language Models to Particular Contextual Regulations
by: Achintalwar, Swapnaja, et al.
Published: (2024)

Beyond Labels: Aligning Large Language Models with Human-like Reasoning
by: Kabir, Muhammad Rafsan, et al.
Published: (2024)

Weak-to-Strong Search: Align Large Language Models via Searching over Small Language Models
by: Zhou, Zhanhui, et al.
Published: (2024)

Unraveling and Mitigating Safety Alignment Degradation of Vision-Language Models
by: Liu, Qin, et al.
Published: (2024)

Branch-Solve-Merge Improves Large Language Model Evaluation and Generation
by: Saha, Swarnadeep, et al.
Published: (2023)

LAMPO: Large Language Models as Preference Machines for Few-shot Ordinal Classification
by: Qin, Zhen, et al.
Published: (2024)

Mitigating Hallucinated Translations in Large Language Models with Hallucination-focused Preference Optimization
by: Tang, Zilu, et al.
Published: (2025)