5 papers
Adaptive Hierarchical Representation Alliance for Multimodal Learning
Chunlei Meng, Pengbin Feng, Jacqueline J. Pang +5
Multimodal models often align language, vision, and audio in a single final-layer latent space, implicitly assuming that task-relevant evidence emerges at the same semantic depth a…
Rethinking Modality Reliability in Multimodal Sentiment Analysis with Incomplete Observations
Chunlei Meng, Jacqueline J. Pang, Pengbin Feng +3
Multimodal Sentiment Analysis (MSA) integrates text, audio, and vision to infer human affect, yet real-world multimodal observations are often incomplete. Existing methods for inco…
Learning-Based Automated Adversarial Red-Teaming for Robustness Evaluation of Large Language Models
Zhang Wei, Hanxuan Chen, Peilu Hu +19
Red-teaming is becoming a central part of large language model (LLM) safety evaluation, yet current practice still relies heavily on expert-written prompts or fixed benchmark suite…
AOI: Context-Aware Multi-Agent Operations via Dynamic Scheduling and Hierarchical Memory Compression
Zishan Bai, Hanxuan Chen, Jiayi Gu +9
Cloud-native systems have made operational work both more powerful and harder to automate: incidents unfold across microservices, logs and metrics arrive faster than operators can…
CoT-X: An Adaptive Framework for Cross-Model Chain-of-Thought Transfer and Optimization
Ziqian Bi, Yinzhi Wang, Tianyang Wang +6
Long Chain-of-Thought (CoT) traces can improve reasoning accuracy, but repeatedly generating them is costly for smaller or latency-constrained language models. This paper studies a…