1 citations · 1 across the 7 of their papers we have counts for
7 papers
CACR:Reinforcing Temporal Answer Grounding in Instructional Video via Candidate-Aware Causal Reasoning
Muge Qi, Rong Fu, Pengbin Feng +7
The task of temporal answer grounding in instructional video (TAGV), which aims to locate precise video segments that respond to natural language queries, is increasingly important…
NeuroSymb-MRG: Differentiable Abductive Reasoning with Active Uncertainty Minimization for Radiology Report Generation
Rong Fu, Yiqing Lyu, Chunlei Meng +9
Automatic generation of radiology reports seeks to reduce clinician workload while improving documentation consistency. Existing methods that adopt encoder-decoder or retrieval-aug…
ModalImmune: Immunity Driven Unlearning via Self Destructive Training
Rong Fu, WeiZhi Tang, Ziming Wang +6
Multimodal systems are vulnerable to partial or complete loss of input channels at deployment, which undermines reliability in real-world settings. This paper presents ModalImmune,…
AdvSynGNN: Structure-Adaptive Graph Neural Nets via Adversarial Synthesis and Self-Corrective Propagation
Rong Fu, Chunlei Meng, Shuo Yin +2
Graph neural networks frequently encounter significant performance degradation when confronted with structural noise or non-homophilous topologies. To address these systemic vulner…
GaiaFlow: Semantic-Guided Diffusion Tuning for Carbon-Frugal Search
Rong Fu, Jia Yee Tan, Chunlei Meng +4
As the burgeoning power requirements of sophisticated neural architectures escalate, the information retrieval community has recognized ecological sustainability as a pivotal prior…
SwiftRepertoire: Few-Shot Immune-Signature Synthesis via Dynamic Kernel Codes
Rong Fu, Yang Li, Yabin Jin +3
Repertoire-level analysis of T cell receptors offers a biologically grounded signal for disease detection and immune monitoring, yet practical deployment is impeded by label sparsi…
Towards Harmonized Uncertainty Estimation for Large Language Models
Rui Li, Jing Long, Muge Qi +4
To facilitate robust and trustworthy deployment of large language models (LLMs), it is essential to quantify the reliability of their generations through uncertainty estimation. Wh…