2 citations · 5 across the 9 of their papers we have counts for
10 papers
Chain-of-Adaptation: Surgical Vision-Language Adaptation with Reinforcement Learning
Jiajie Li, Chenhui Xu, Meihuan Liu +1
Conventional fine-tuning on domain-specific datasets can inadvertently alter a model's pretrained multimodal priors, leading to reduced generalization. To address this, we propose…
Selective Prior Synchronization via SYNC Loss
Ishan Mishra, Jiajie Li, Deepak Mishra +1
Prediction under uncertainty is a critical requirement for the deep neural network to succeed responsibly. This paper focuses on selective prediction, which allows DNNs to make inf…
Auto-Prompt Ensemble for LLM Judge
Jiajie Li, Huayi Zhang, Peng Lin +2
We present a novel framework that improves the reliability of LLM judges by selectively augmenting LLM with auxiliary evaluation dimensions. Existing LLM judges often miss crucial…
Towards Understanding Multi-Round Large Language Model Reasoning: Approximability, Learnability and Generalizability
Chenhui Xu, Dancheng Liu, Jiajie Li +3
Recent advancements in cognitive science and multi-round reasoning techniques for Large Language Models (LLMs) suggest that iterative thinking processes improve problem-solving per…
Sub-Sequential Physics-Informed Learning with State Space Model
Chenhui Xu, Dancheng Liu, Yuting Hu +4
Physics-Informed Neural Networks (PINNs) are a kind of deep-learning-based numerical solvers for partial differential equations (PDEs). Existing PINNs often suffer from failure mod…
Recognize Any Surgical Object: Unleashing the Power of Weakly-Supervised Data
Jiajie Li, Brian R Quaranto, Chenhui Xu +5
We present RASO, a foundation model designed to Recognize Any Surgical Object, offering robust open-set recognition capabilities across a broad range of surgical procedures and obj…
LLaVA-Surg: Towards Multimodal Surgical Assistant via Structured Surgical Video Learning
Jiajie Li, Garrett Skinner, Gene Yang +4
Multimodal large language models (LLMs) have achieved notable success across various domains, while research in the medical field has largely focused on unimodal images. Meanwhile,…
Large Language Models have Intrinsic Self-Correction Ability
Dancheng Liu, Amir Nassereldine, Ziming Yang +8
Large language models (LLMs) have attracted significant attention for their exceptional abilities in various natural language processing tasks, but they suffer from hallucinations…
xMLP: Revolutionizing Private Inference with Exclusive Square Activation
Jiajie Li, Jinjun Xiong
Private Inference (PI) enables deep neural networks (DNNs) to work on private data without leaking sensitive information by exploiting cryptographic primitives such as multi-party…
Ensembler: Protect Collaborative Inference Privacy from Model Inversion Attack via Selective Ensemble
Dancheng Liu, Chenhui Xu, Jiajie Li +2
For collaborative inference through a cloud computing platform, it is sometimes essential for the client to shield its sensitive information from the cloud provider. In this paper,…