activity
20242026
collaborators

9 papers

cs.AI2026

SpecAlign: Efficient Specification-Grounded Alignment of Large Language Models via Synthetic Data

Wenjie Wang, Yue Huang, Zhengqing Yuan +6

As large language models (LLMs) are increasingly deployed in real-world applications, alignment is no longer governed by a single universal notion of safety or helpfulness, but ins…

cs.SE2026

UXBench: Measuring the Actionability of LLM-Generated UX Critiques

Wenjie Wang, Yue Huang, Zipeng Ling +11

Large language models (LLMs) are increasingly deployed as UX judges that inspect interfaces, diagnose usability problems, and propose repairs. Yet no controlled benchmark measures…

cs.LG2026

Reward Transport: Property Control in Flow Matching via Noise-Space Alignment

Kehan Guo, Yili Shen, Yujun Zhou +4

The coupling in flow matching -- the rule pairing noise vectors with data points -- is typically treated as a computational choice. We show that this coupling can instead serve as…

cs.LG2026

Models Know Their Shortcuts: Deployment-Time Shortcut Mitigation

Jiayi Li, Shijie Tang, Gün Kaynar +2

Pretrained text encoders are prone to shortcut learning, relying on token-label correlations that fail once the distribution shifts in deployment. Existing shortcut mitigation meth…

cs.CL2026

The Memory Curse: How Expanded Recall Erodes Cooperative Intent in LLM Agents

Jiayuan Liu, Tianqin Li, Shiyi Du +7

Context window expansion is often treated as a straightforward capability upgrade for LLMs, but we find it systematically fails in multi-agent social dilemmas. Across 7 LLMs and 4…

cs.LG2026

Why Search When You Can Transfer? Amortized Agentic Workflow Design from Structural Priors

Shiyi Du, Jiayuan Liu, Weihua Du +6

Automated agentic workflow design currently relies on per-task iterative search, which is computationally prohibitive and fails to reuse structural knowledge across tasks. We obser…