collaborators

12 papers

cs.AI2026

Arena-T2I Hard: Benchmarking and Improving Faithfulness with Dependency-Aware Checklist

Yuanhao Ban, Tong Xie, Sohyun An +6

Faithfulness -- how precisely a generated image aligns with its prompt -- is increasingly central to the real-world utility of text-to-image (T2I) models. Existing faithfulness ben…

cs.LG2026

DualEval: Joint Model-Item Calibration for Unified LLM Evaluation

Aaron J. Li, Hao Huang, Youngmin Park +6

Current LLM evaluation relies on two complementary but often disconnected signals: static benchmarks with objective correctness labels and arena-style preference data that better r…

cs.CL2026

Search Arena: Analyzing Search-Augmented LLMs

Mihran Miroyan, Tsung-Han Wu, Logan King +8

Search-augmented language models combine web search with Large Language Models (LLMs) to improve response groundedness and freshness. However, analyzing these systems remains chall…

cs.SE2025

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…

cs.SD2025

Music Arena: Live Evaluation for Text-to-Music

Yonghyun Kim, Wayne Chi, Anastasios N. Angelopoulos +5

We present Music Arena, an open platform for scalable human preference evaluation of text-to-music (TTM) models. Soliciting human preferences via listening studies is the gold stan…

cs.CL2025

OR-Bench: An Over-Refusal Benchmark for Large Language Models

Justin Cui, Wei-Lin Chiang, Ion Stoica +1

Large Language Models (LLMs) require careful safety alignment to prevent malicious outputs. While significant research focuses on mitigating harmful content generation, the enhance…