8 papers · 1 filter
Distributionally Robust Mixture-of-Experts Training
Xin Teng, Muxiao Li, Hongyi Wen
Mixture-of-Experts (MoE) transformers scale capacity by activating only a few experts per token, but this sparsity creates a hidden reliability problem: when routing is imperfect,…
Coherence-Aware Distributional Evaluation of Open-Ended Text Generation
Jinnuo Liu, Junhao Zhu, Weifeng Jiang +2
Existing open-ended generation metrics measure likelihood, lexical diversity, or distributional similarity in generic representation space, yet can miss fundamental dimensions of q…
EvoGenUI-Bench: Evaluating LLMs as Multi-Turn Generative UI Assistants
Yue Peng, Lanke Xia, Zihan Wang +3
Large language models can generate interactive web interfaces, but reliable generative UI requires maintaining an executable artifact as user requests evolve. We introduce EvoGenUI…
Toward Latent Language Model Skills Steering and Optimization: An Empirical Study
Xunyi Jiang, Junda Wu, Yuxin Xiong +6
Skills, as a useful abstraction for the procedural capabilities of large language models (LLMs), capture how models perform structured, multi-step reasoning and program execution.…
Histogram-constrained Image Generation
Haoming Liu, Yuanhe Guo, Yijia Cao +2
Diffusion models have emerged as a dominant paradigm in generative modeling, enabling high-fidelity sampling from complex data distributions. Despite impressive capabilities, contr…
Evaluating Interactivity: Toward Automated Assessment of AI-Generated Explorable Explanations
Xiaozao Wang, Zhewei Wang, Hongyi Wen
While large language models now enable rapid generation of interactive learning materials, evaluating the interaction quality of these explorable explanations remains an open chall…
NovelAPIBench: Diagnosing How A Code LLM Learns to Use Novel APIs
Jinnuo Liu, Yue Peng, Jinhan Niu +1
Rapidly evolving software libraries require coding language models to use unfamiliar APIs. Yet failed solutions alone tell us little about what API knowledge models need or how to…
SHAPE: Unifying Safety, Helpfulness and Pedagogy for Educational LLMs
Sihang Zhao, Kangrui Yu, Youliang Yuan +2
Large Language Models (LLMs) have been widely explored in educational scenarios. We identify a critical vulnerability in current educational LLMs, pedagogical jailbreaks, where stu…