1 citations · 1 across the 7 of their papers we have counts for
10 papers
Fix, Not Just Resample: Bounded Compiler-Guided Repair in Lean 4
Haotian Deng, Chris Farber, Sonal Narasimha +2
Automated theorem provers often rely on sampling language models, but proof assistants like Lean reject each failed step with a precise error message --- information that pure samp…
Can Vision-Language Models Stay Helpful When Facing Implicit Risks? Intent-Privilege OPSD for Efficient Safety-Helpfulness Alignment
Haotian Deng, Wenbin Xing, Gang Xu +5
Vision-Language Models (VLMs) remain vulnerable to cross-modal implicit risks: visual and textual inputs that appear benign in isolation can jointly elicit unsafe responses. Existi…
Omni-fMRI: A Universal Atlas-Free fMRI Foundation Model
Mo Wang, Wenhao Ye, Junfeng Xia +6
Self-supervised fMRI foundation models have shown promising transfer performance, yet most rely on predefined region-level parcellations that discard fine-grained voxel information…
Understanding Generalization from Embedding Dimension and Distributional Convergence
Junjie Yu, Zhuoli Ouyang, Haotian Deng +5
Deep neural networks often generalize well despite heavy over-parameterization, challenging classical parameter-based analyses. We study generalization from a representation-centri…
Local Intrinsic Dimension of Representations Predicts Alignment and Generalization in AI Models and Human Brain
Junjie Yu, Wenxiao Ma, Chen Wei +4
Recent work has found that neural networks with stronger generalization tend to exhibit higher representational alignment with one another across architectures and training paradig…
Rubric-Conditioned LLM Grading: Alignment, Uncertainty, and Robustness
Haotian Deng, Chris Farber, Jiyoon Lee +1
Automated short-answer grading (ASAG) remains a challenging task due to the linguistic variability of student responses and the need for nuanced, rubric-aligned partial credit. Whi…
AutoICE: Automatically Synthesizing Verifiable C Code via LLM-driven Evolution
Weilin Luo, Xueyi Liang, Haotian Deng +2
Automatically synthesizing verifiable code from natural language requirements ensures software correctness and reliability while significantly lowering the barrier to adopting the…
Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions
Haotian Deng, Chi Zhang, Chen Wei +1
A fundamental challenge in affective cognitive science is to develop models that accurately capture the relationship between external emotional stimuli and human internal experienc…
Scale-Invariance Drives Convergence in AI and Brain Representations
Junjie Yu, Wenxiao Ma, Jianyu Zhang +4
Despite variations in architecture and pretraining strategies, recent studies indicate that large-scale AI models often converge toward similar internal representations that also a…
Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering and Manipulating Human Perceptual Variability
Chen Wei, Chi Zhang, Jiachen Zou +3
Human decision-making in cognitive tasks and daily life exhibits considerable variability, shaped by factors such as task difficulty, individual preferences, and personal experienc…