4 papers
Self-Authored Verification Is Unreliable in Heuristic Self-Improving Agents
Diandian Guo, Cong Cao, Fangfang Yuan +3
Self-improving agents accumulate capability by repeatedly rewriting procedural policies, controllers, or heuristic rules. They typically rely on self-authored tests or metrics to d…
From Large to Super-Tiny: End-to-End Optimization for Cost-Efficient LLMs
Jiliang Ni, Jiachen Pu, Zhongyi Yang +7
Large Language Models (LLMs) have significantly advanced artificial intelligence by optimizing traditional Natural Language Processing (NLP) workflows, facilitating their integrati…
Can Multimodal Large Language Model Think Analogically?
Diandian Guo, Cong Cao, Fangfang Yuan +4
Analogical reasoning, particularly in multimodal contexts, is the foundation of human perception and creativity. Multimodal Large Language Model (MLLM) has recently sparked conside…
Efficient Byzantine-Resilient Stochastic Gradient Desce
Kaiyun Li, Xiaojun Chen, Ye Dong +3
Distributed Learning often suffers from Byzantine failures, and there have been a number of works studying the problem of distributed stochastic optimization under Byzantine failur…