most citedSelf-Refine: Iterative Refinement with Self-Feedback

221 citations · 227 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2023

STEER: Unified Style Transfer with Expert Reinforcement

Skyler Hallinan, Faeze Brahman, Ximing Lu +3

While text style transfer has many applications across natural language processing, the core premise of transferring from a single source style is unrealistic in a real-world setti…

cs.AI20233 cited

LLMSTEP: LLM proofstep suggestions in Lean

Sean Welleck, Rahul Saha

We present LLMSTEP, a tool for integrating a language model into the Lean proof assistant. LLMSTEP is a Lean 4 tactic that sends a user's proof state to a server hosting a language…

cs.CL2023221 cited

Self-Refine: Iterative Refinement with Self-Feedback

Aman Madaan, Niket Tandon, Prakhar Gupta +13

Like humans, large language models (LLMs) do not always generate the best output on their first try. Motivated by how humans refine their written text, we introduce Self-Refine, an…

cs.CL20212 cited

NeuroLogic A*esque Decoding: Constrained Text Generation with Lookahead Heuristics

Ximing Lu, Sean Welleck, Peter West +9

The dominant paradigm for neural text generation is left-to-right decoding from autoregressive language models. Constrained or controllable generation under complex lexical constra…

cs.CL20211 cited

Prompt Waywardness: The Curious Case of Discretized Interpretation of Continuous Prompts

Daniel Khashabi, Shane Lyu, Sewon Min +8

Fine-tuning continuous prompts for target tasks has recently emerged as a compact alternative to full model fine-tuning. Motivated by these promising results, we investigate the fe…