:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Zhang, Wenbo, Majumdar, Aditya, Yadav, Amulya
Format:	Preprint
Published:	2024
Subjects:	Computation and Language Artificial Intelligence Machine Learning
Online Access:	https://arxiv.org/abs/2411.09073
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

The Hardness of Achieving Impact in AI for Social Impact Research: A Ground-Level View of Challenges & Opportunities
by: Majumdar, Aditya, et al.
Published: (2025)

Peering Through Preferences: Unraveling Feedback Acquisition for Aligning Large Language Models
by: Bansal, Hritik, et al.
Published: (2023)

Improving Reinforcement Learning from Human Feedback with Efficient Reward Model Ensemble
by: Zhang, Shun, et al.
Published: (2024)

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

Training Large Language Models for Reasoning through Reverse Curriculum Reinforcement Learning
by: Xi, Zhiheng, et al.
Published: (2024)

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

DISPO: Enhancing Training Efficiency and Stability in Reinforcement Learning for Large Language Model Mathematical Reasoning
by: Karaman, Batuhan K., et al.
Published: (2026)

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

RLPF: Reinforcement Learning from Prediction Feedback for User Summarization with LLMs
by: Wu, Jiaxing, et al.
Published: (2024)

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

RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedback
by: Lee, Harrison, et al.
Published: (2023)

CHAI: Command Hijacking against embodied AI
by: Burbano, Luis, et al.
Published: (2025)

Improving Code Generation by Training with Natural Language Feedback
by: Chen, Angelica, et al.
Published: (2023)

UltraFeedback: Boosting Language Models with Scaled AI Feedback
by: Cui, Ganqu, et al.
Published: (2023)

LatentBreak: Jailbreaking Large Language Models through Latent Space Feedback
by: Mura, Raffaele, et al.
Published: (2025)

Speaking the Same Language: Leveraging LLMs in Standardizing Clinical Data for AI
by: Sett, Arindam, et al.
Published: (2024)

Self-play with Execution Feedback: Improving Instruction-following Capabilities of Large Language Models
by: Dong, Guanting, et al.
Published: (2024)

RLHF Deciphered: A Critical Analysis of Reinforcement Learning from Human Feedback for LLMs
by: Chaudhari, Shreyas, et al.
Published: (2024)

Reinforcement Learning with Backtracking Feedback
by: Sel, Bilgehan, et al.
Published: (2026)

Creating and Evaluating Code-Mixed Nepali-English and Telugu-English Datasets for Abusive Language Detection Using Traditional and Deep Learning Models
by: Pandey, Manish, et al.
Published: (2025)

A Multilingual Sentiment Lexicon for Low-Resource Language Translation using Large Languages Models and Explainable AI
by: Malinga, Melusi, et al.
Published: (2024)

CodeIt: Self-Improving Language Models with Prioritized Hindsight Replay
by: Butt, Natasha, et al.
Published: (2024)

Adversarial Reinforcement Learning for Large Language Model Agent Safety
by: Wang, Zizhao, et al.
Published: (2025)

Paraphrase and Aggregate with Large Language Models for Minimizing Intent Classification Errors
by: Yadav, Vikas, et al.
Published: (2024)

Steering Large Language Models for Machine Translation Personalization
by: Scalena, Daniel, et al.
Published: (2025)

Hephaestus: Improving Fundamental Agent Capabilities of Large Language Models through Continual Pre-Training
by: Zhuang, Yuchen, et al.
Published: (2025)

VietMix: A Naturally-Occurring Parallel Corpus and Augmentation Framework for Vietnamese-English Code-Mixed Machine Translation
by: Tran, Hieu, et al.
Published: (2025)

Knowledgeable Agents by Offline Reinforcement Learning from Large Language Model Rollouts
by: Pang, Jing-Cheng, et al.
Published: (2024)

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

Improving Large Language Model Safety with Contrastive Representation Learning
by: Simko, Samuel, et al.
Published: (2025)

Rethinking Data Mixing from the Perspective of Large Language Models
by: Xu, Yuanjian, et al.
Published: (2026)

Distributionally Robust Reinforcement Learning with Human Feedback
by: Mandal, Debmalya, et al.
Published: (2025)

Code Simulation Challenges for Large Language Models
by: La Malfa, Emanuele, et al.
Published: (2024)

Parameter Efficient Reinforcement Learning from Human Feedback
by: Sidahmed, Hakim, et al.
Published: (2024)

Detecting Data Contamination from Reinforcement Learning Post-training for Large Language Models
by: Tao, Yongding, et al.
Published: (2025)

Reinforcement Learning for Reasoning in Large Language Models with One Training Example
by: Wang, Yiping, et al.
Published: (2025)

Group-Aware Reinforcement Learning for Output Diversity in Large Language Models
by: Anschel, Oron, et al.
Published: (2025)

Adaptive Pruning for Large Language Models with Structural Importance Awareness
by: Zheng, Haotian, et al.
Published: (2024)

AceReason-Nemotron: Advancing Math and Code Reasoning through Reinforcement Learning
by: Chen, Yang, et al.
Published: (2025)

Reinforcement Learning Enhanced LLMs: A Survey
by: Wang, Shuhe, et al.
Published: (2024)