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Found 5 papers, 1 papers with code
Beyond Sparse Rewards: Enhancing Reinforcement Learning with Language Model Critique in Text Generation
We investigate this approach under two different settings: one where the policy model is smaller and is paired with a more powerful critic model, and another where a single language model fulfills both roles.
Fusion-Eval: Integrating Evaluators with LLMs
Evaluating natural language systems poses significant challenges, particularly in the realms of natural language understanding and high-level reasoning.
Critique Ability of Large Language Models
In the era of large language models (LLMs), this study explores the ability of LLMs to deliver accurate critiques across various tasks.
Towards an On-device Agent for Text Rewriting
Large Language Models (LLMs) have demonstrated impressive capabilities for text rewriting.
RewriteLM: An Instruction-Tuned Large Language Model for Text Rewriting
In this work, we develop new strategies for instruction tuning and reinforcement learning to better align LLMs for cross-sentence rewriting tasks using diverse wording and structures expressed through natural languages including 1) generating rewriting instruction data from Wiki edits and public corpus through instruction generation and chain-of-thought prompting; 2) collecting comparison data for reward model training through a new ranking function.
