12 papers
From Preference to Reciprocity: Decentralized Matching with Empirically Grounded LLM-agent Based Modeling
Wangxuan Fan, Xiaoyu Nie, Zhoutian Shi +5
Bipartite matching is a fundamental problem in game theory and market design. Classical approaches such as Gale--Shapley assume complete preferences and centralized computation, wh…
Why Vision Fails as a Universal Bridge: Rectifying Modality Asynchrony in Multilingual MLLMs
Yihang Du, Juhao Liang, Zhengzhao Lai +2
Multimodal large language models (MLLMs) exhibit substantial performance degradation in non-English visual reasoning, despite the strong multilingual competence of their text-only…
Learning to Select, Not Relearn: Hard-Routed Mixtures of Reasoning LoRAs
Seyed Alireza Molavi, Zhan Su, Yan Hu +3
Composing independently trained LoRA adapters into a single large language model is useful for multi-domain adaptation, especially when the original training data cannot be shared.…
Does higher interpretability imply better utility? A Pairwise Analysis on Sparse Autoencoders
Xu Wang, Yan Hu, Benyou Wang +1
Sparse Autoencoders (SAEs) are widely used to steer large language models (LLMs), based on the assumption that their interpretable features naturally enable effective model behavio…
Can Multimodal LLMs See Materials Clearly? A Multimodal Benchmark on Materials Characterization
Zhengzhao Lai, Youbin Zheng, Zhenyang Cai +5
Materials characterization is fundamental to acquiring materials information, revealing the processing-microstructure-property relationships that guide material design and optimiza…
PrinciplismQA: A Philosophy-Grounded Approach to Assessing LLM-Human Clinical Medical Ethics Alignment
Chang Hong, Minghao Wu, Qingying Xiao +5
As medical LLMs transition to clinical deployment, assessing their ethical reasoning capability becomes critical. While achieving high accuracy on knowledge benchmarks, LLMs lack v…
Model Unlearning via Sparse Autoencoder Subspace Guided Projections
Xu Wang, Zihao Li, Benyou Wang +2
Large language models (LLMs) store vast amounts of information, making them powerful yet raising privacy and safety concerns when selective knowledge removal is required. Existing…
Do LLMs Triage Like Clinicians? A Dynamic Study of Outpatient Referral
Xiaoxiao Liu, Qingying Xiao, Bingquan Zhang +8
Outpatient referral (OR) is a core clinical workflow that assigns patients to hospital departments under incomplete and evolving information, yet it is commonly simplified as a sta…
Towards Understanding Fine-Tuning Mechanisms of LLMs via Circuit Analysis
Xu Wang, Yan Hu, Wenyu Du +3
Fine-tuning significantly improves the performance of Large Language Models (LLMs), yet its underlying mechanisms remain poorly understood. This paper aims to provide an in-depth i…
TwinMarket: A Scalable Behavioral and Social Simulation for Financial Markets
Yuzhe Yang, Yifei Zhang, Minghao Wu +5
The study of social emergence has long been a central focus in social science. Traditional modeling approaches, such as rule-based Agent-Based Models (ABMs), struggle to capture th…
Federated Linear Dueling Bandits
Xuhan Huang, Yan Hu, Zhiyan Li +3
Contextual linear dueling bandits have recently garnered significant attention due to their widespread applications in important domains such as recommender systems and large langu…
BlenderLLM: Training Large Language Models for Computer-Aided Design with Self-improvement
Yuhao Du, Shunian Chen, Wenbo Zan +6
The application of Large Language Models (LLMs) in Computer-Aided Design (CAD) remains an underexplored area, despite their remarkable advancements in other domains. In this paper,…