6 papers
ContextGuard: Structured Self-Auditing for Context Learning in Language Models
Hongbo Jin, Chi Wang, Haoran Tang +5
Recent benchmarks reveal that despite strong reasoning capabilities, large language models (LLMs) still struggle to faithfully apply complex contextual knowledge. These failures ar…
Context-CoT: Enhancing Context Learning via High-Quality Reasoning Synthesis
Hongbo Jin, Mingnan Zhu, Jingqi Tian +6
While LLMs excel at reasoning over prompts using static pretrained knowledge, they struggle significantly with context learning-the ability to dynamically extract, internalize, and…
VISD: Enhancing Video Reasoning via Structured Self-Distillation
Hao Lin, Kunyang Lv, Xu Jiang +5
Training VideoLLMs for complex reasoning remains challenging due to sparse sequence level rewards and the lack of fine grained credit assignment over long, temporally grounded reas…
STARS: Spike Tail-Aware Relational Synthesis for ANN-to-SNN Data-Free Knowledge Distillation
Shuhan Ye, Yi Yu, Qixin Zhang +5
SNNs promise energy-efficient and low-latency inference, but their performance still trails that of ANNs. ANN-to-SNN knowledge distillation helps narrow this gap, yet the original…
Neural Collapse in Test-Time Adaptation
Xiao Chen, Zhongjing Du, Jiazhen Huang +4
Test-Time Adaptation (TTA) enhances model robustness to out-of-distribution (OOD) data by updating the model online during inference, yet existing methods lack theoretical insights…
SIT-FER: Integration of Semantic-, Instance-, Text-level Information for Semi-supervised Facial Expression Recognition
Sixian Ding, Xu Jiang, Zhongjing Du +3
Semi-supervised deep facial expression recognition (SS-DFER) has gained increasingly research interest due to the difficulty in accessing sufficient labeled data in practical setti…