1 citations · 2 across the 6 of their papers we have counts for
4 papers · 1 filter
EDIT-Bench: Evaluating LLM Abilities to Perform Real-World Instructed Code Edits
Wayne Chi, Valerie Chen, Ryan Shar +8
Instructed code editing, where LLMs directly modify a developer's existing code based on a user instruction, is becoming a widely used interaction mode in AI coding assistants. How…
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…
Copilot Arena: A Platform for Code LLM Evaluation in the Wild
Wayne Chi, Valerie Chen, Anastasios Nikolas Angelopoulos +7
Evaluating in-the-wild coding capabilities of large language models (LLMs) is a challenging endeavor with no clear solution. We introduce Copilot Arena, a platform to collect user…
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…