From the 1 of 11 linked papers with an AI index.
11 papers
Dynamic Context Adapters: Efficiently Infusing History into Vision-and-Language Models
Yuhang Song, Bor-Jiun Lin, Jiaxu Liu +3
Historical context integration presents a fundamental challenge for Vision-Language Models (VLMs) in sequential decision-making tasks. Current VLMs process visual inputs independen…
Crossing the Margin Cliff: Toward Relearn-Robust LLM Unlearning via Margin Calibration
Xiangyu Yin, Jiaxu Liu, Zhen Chen +1
The paper identifies a systematic “margin cliff” that makes large language model unlearning vulnerable to relearn attacks and proposes Margin Calibration, a plug‑in method that add…
READER: Dynamic LLM Provenance from Query-Varying Interactions
Jiaxu Liu, Sunnan Mu, Dong Huang +3
Existing black-box LLM provenance methods achieve comparability by querying every candidate model with the same diagnostic prompts. In deployment, auditors inherit a different evid…
CeTAD: Towards Certified Toxicity-Aware Distance in Vision Language Models
Xiangyu Yin, Jiaxu Liu, Zhen Chen +4
Recent advances in large vision-language models (VLMs) have demonstrated remarkable success across a wide range of visual understanding tasks. However, the robustness of these mode…
Enhancing Robust Fairness via Confusional Spectral Regularization
Gaojie Jin, Sihao Wu, Jiaxu Liu +2
Recent research has highlighted a critical issue known as ``robust fairness", where robust accuracy varies significantly across different classes, undermining the reliability of de…
Integrating Object Detection Modality into Visual Language Model for Enhanced Autonomous Driving Agent
Linfeng He, Yiming Sun, Sihao Wu +2
In this paper, we propose a novel framework for enhancing visual comprehension in autonomous driving systems by integrating visual language models (VLMs) with additional visual per…