activity
20222026
most citedStructEval: Benchmarking LLMs' Capabilities to Generate Structural Outputs

2 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2026

UniMaia: Steering Chess Policies with Language for Human-like Play

Sherman Siu, Lesley Istead

Recent advances in large language models have enabled natural language to serve as a flexible interface for controlling complex systems, but often at the cost of large-scale multim…

cs.SE2025★ 2 cited

StructEval: Benchmarking LLMs' Capabilities to Generate Structural Outputs

Jialin Yang, Dongfu Jiang, Lipeng He +17

As Large Language Models (LLMs) become integral to software development workflows, their ability to generate structured outputs has become critically important. We introduce Struct…

cs.CV2024

MEGA-Bench: Scaling Multimodal Evaluation to over 500 Real-World Tasks

Jiacheng Chen, Tianhao Liang, Sherman Siu +13

We present MEGA-Bench, an evaluation suite that scales multimodal evaluation to over 500 real-world tasks, to address the highly heterogeneous daily use cases of end users. Our obj…

cs.CV2024

VideoScore: Building Automatic Metrics to Simulate Fine-grained Human Feedback for Video Generation

Xuan He, Dongfu Jiang, Ge Zhang +16

The recent years have witnessed great advances in video generation. However, the development of automatic video metrics is lagging significantly behind. None of the existing metric…

cs.CL2022

Towards automating Codenames spymasters with deep reinforcement learning

Sherman Siu

Although most reinforcement learning research has centered on competitive games, little work has been done on applying it to co-operative multiplayer games or text-based games. Cod…