43 citations · 161 across the 42 of their papers we have counts for
14 papers · 1 filter
UNISON: A Unified Framework for Learning from Scored Bags
Ofek Kirshenboim, Or Shkuri, Shani Finkelshtein +1
We introduce UNISON, a unified framework that bridges multiple instance learning and recommendation systems by treating both as instances of learning from scored bag collections of…
Complex Problem Solving in Large Language Models: A Statistical Control Survey and Diagnostic Framework
Jiazhang Cai, Tao Wang, Ruidong Zhang +35
Complex problem solving (CPS) with large language models (LLMs) is often framed as a matter of stronger reasoning or longer generation. Yet early-step error amplification, prompt b…
Who Speaks for the Pruned? Visual Token Pruning as Coverage Optimization
Qingchan Zhu, Weihang You, Hanqi Jiang +3
Visual token pruning reduces the inference cost of vision-language models (VLMs), but most methods only ask which tokens to keep. This retained-token view can keep redundant high-s…
Identifying the Sign of Coherent Over-Rotations with Logarithmically Many Pauli Settings
Yi Pan, Meng Hsiu Tsai, Weihang You +6
Calibrating a quantum processor means estimating gate-error parameters from data, and a hard-to-estimate parameter is usually assumed to leave a weak signature more repetitions wil…
An Interaction Language Model: Mechanism Discovery from Statistical Patterns of Physical Interactions
Triparna Ganguly, Hanqi Jiang, Xinliang Li +5
Interactions among building blocks in physical, chemical, and biological systems follow structured patterns interpretable as a learnable language: just as language models learn whi…
Toward Vibe Medicine: A Self-Evolving Multi-Agent Framework for Clinical Decision Support
Qianxue Zhang, Yiming Ren, Shihuan Qin +18
In recent years, the advances of large language models and autonomous agents have revolutionized the healthcare field, facilitating diagnosis and improving treatment results. Howev…
World Models: A Comprehensive Survey of Architectures, Methodologies, Reasoning Paradigms, and Applications
Arif Hassan Zidan, Yi Pan, Hanqi Jiang +23
World models, internal simulators that learn the structure and dynamics of an environment, have emerged as a central paradigm in the pursuit of artificial general intelligence, ena…
MedVIGIL: Evaluating Trustworthy Medical VLMs Under Broken Visual Evidence
Hanqi Jiang, Junhao Chen, Mingyu Kang +12
Medical vision--language models (VLMs) are usually evaluated on intact image--question pairs, but trustworthy clinical use requires a stronger property: a model must recognise when…
Thinking with Gaze: Sequential Eye-Tracking as Visual Reasoning Supervision for Medical VLMs
Yiwei Li, Yifan Zhou, Huaqin Zhao +6
Vision--language models (VLMs) process images as visual tokens, yet their intermediate reasoning is often carried out in text, which can be suboptimal for visually grounded radiolo…
Neural Functional Alignment Space: Brain-Referenced Representation of Artificial Neural Networks
Ruiyu Yan, Hanqi Jiang, Yi Pan +4
We propose the Neural Functional Alignment Space (NFAS), a brain-referenced representational framework for characterizing artificial neural networks on equal functional grounds. NF…
SYNAPSE: Empowering LLM Agents with Episodic-Semantic Memory via Spreading Activation
Hanqi Jiang, Junhao Chen, Yi Pan +8
While Large Language Models (LLMs) excel at generalized reasoning, standard retrieval-augmented approaches fail to address the disconnected nature of long-term agentic memory. To b…
ViThinker: Active Vision-Language Reasoning via Dynamic Perceptual Querying
Weihang You, Qingchan Zhu, David Liu +3
Chain-of-Thought (CoT) reasoning excels in language models but struggles in vision-language models due to premature visual-to-text conversion that discards continuous information s…
Large Language Models for Assisting American College Applications
Zhengliang Liu, Weihang You, Peng Shu +14
American college applications require students to navigate fragmented admissions policies, repetitive and conditional forms, and ambiguous questions that often demand cross-referen…
Achieving Fine-grained Cross-modal Understanding through Brain-inspired Hierarchical Representation Learning
Weihang You, Hanqi Jiang, Yi Pan +3
Understanding neural responses to visual stimuli remains challenging due to the inherent complexity of brain representations and the modality gap between neural data and visual inp…