1 citations · 2 across the 6 of their papers we have counts for
4 papers · 1 filter
Interaction-as-a-Judge
Wayne Chi, I-Hung Hsu, Li Chen +6
Coding agents are tasked with producing sophisticated interactive applications such as websites, desktop applications, and games. While humans assess these applications interactive…
Autellix: An Efficient Serving Engine for LLM Agents as General Programs
Michael Luo, Xiaoxiang Shi, Colin Cai +8
Large language model (LLM) applications are evolving beyond simple chatbots into dynamic, general-purpose agentic programs, which scale LLM calls and output tokens to help AI agent…
Exploring and Mitigating Adversarial Manipulation of Voting-Based Leaderboards
Yangsibo Huang, Milad Nasr, Anastasios Angelopoulos +10
It is now common to evaluate Large Language Models (LLMs) by having humans manually vote to evaluate model outputs, in contrast to typical benchmarks that evaluate knowledge or ski…
How to Evaluate Reward Models for RLHF
Evan Frick, Tianle Li, Connor Chen +6
We introduce a new benchmark for reward models that quantifies their ability to produce strong language models through RLHF (Reinforcement Learning from Human Feedback). The gold-s…