27 papers
()-Parametric Multi-Task Optimization: Joint Search in Solution and Infinite Task Spaces
Tingyang Wei, Jiao Liu, Abhishek Gupta +2
Multi-task optimization is typically characterized by a fixed and finite set of tasks. The present paper relaxes this condition by considering a non-fixed and potentially infinite…
PromptDyG: Test-Time Prompt Adaptation on Dynamic Graphs
Guoguo Ai, Chaoxi Niu, Hui Yan +3
Activities in numerous evolving systems can be represented as dynamic graphs in snapshot form at different time intervals, i.e., discrete-time dynamic graphs (DTDGs). Existing meth…
Hierarchically Robust Zero-shot Vision-language Models
Junhao Dong, Yifei Zhang, Hao Zhu +2
Vision-Language Models (VLMs) can perform zero-shot classification but are susceptible to adversarial attacks. While robust fine-tuning improves their robustness, existing approach…
Finding Sets of Pareto Sets in Real-World Scenarios -- A Multitask Multiobjective Perspective
Jiao Liu, Yew Soon Ong, Melvin Wong
Recently, evolutionary multitasking has been employed to generate a ``set of Pareto sets" (SOS) for machine learning models, addressing diverse task settings across heterogeneous e…
ExpertFlow: Efficient Mixture-of-Experts Inference via Predictive Expert Caching and Token Scheduling
Xin He, Shunkang Zhang, Kaijie Tang +8
Sparse Mixture-of-Experts (MoE) models can outperform dense large language models at similar computation by activating only a small set of experts per token. However, stacking many…
Information Fidelity in Tool-Using LLM Agents: A Martingale Analysis of the Model Context Protocol
Flint Xiaofeng Fan, Cheston Tan, Roger Wattenhofer +1
As AI agents powered by large language models (LLMs) increasingly use external tools for high-stakes decisions, a critical reliability question arises: how do errors propagate acro…