7 citations · 14 across the 13 of their papers we have counts for
4 papers · 1 filter
Dynamic Rewarding with Prompt Optimization Enables Tuning-free Self-Alignment of Language Models
Somanshu Singla, Zhen Wang, Tianyang Liu +3
Aligning Large Language Models (LLMs) traditionally relies on costly training and human preference annotations. Self-alignment seeks to reduce these expenses by enabling models to…
LalaEval: A Holistic Human Evaluation Framework for Domain-Specific Large Language Models
Chongyan Sun, Ken Lin, Shiwei Wang +3
This paper introduces LalaEval, a holistic framework designed for the human evaluation of domain-specific large language models (LLMs). LalaEval proposes a comprehensive suite of e…
Self-MoE: Towards Compositional Large Language Models with Self-Specialized Experts
Junmo Kang, Leonid Karlinsky, Hongyin Luo +7
We present Self-MoE, an approach that transforms a monolithic LLM into a compositional, modular system of self-specialized experts, named MiXSE (MiXture of Self-specialized Experts…
LLM Reasoners: New Evaluation, Library, and Analysis of Step-by-Step Reasoning with Large Language Models
Shibo Hao, Yi Gu, Haotian Luo +9
Generating accurate step-by-step reasoning is essential for Large Language Models (LLMs) to address complex problems and enhance robustness and interpretability. Despite the flux o…