3 citations · 6 across the 15 of their papers we have counts for
4 papers · 1 filter
When Does Task-Aware Imputation Matter? An Analysis of Robustness Under Train-Test Mismatch
Maria V. Salvador, Ana F. Sequeira, Jaime S. Cardoso
Missing data is a pervasive challenge in machine learning, often degrading predictive performance and complicating model deployment. Most existing approaches treat imputation as a…
d3LLM: Ultra-Fast Diffusion LLM using Pseudo-Trajectory Distillation
Yu-Yang Qian, Junda Su, Lanxiang Hu +4
Diffusion large language models (dLLMs) offer capabilities beyond those of autoregressive (AR) LLMs, such as parallel decoding and random-order generation. However, realizing these…
Stronger-MAS: Multi-Agent Reinforcement Learning for Collaborative LLMs
Yujie Zhao, Lanxiang Hu, Yang Wang +4
Multi-agent systems (MAS) and reinforcement learning (RL) are widely used to enhance the agentic capabilities of large language models (LLMs). MAS improves task performance through…
TrimLLM: Progressive Layer Dropping for Domain-Specific LLMs
Lanxiang Hu, Tajana Rosing, Hao Zhang
Specializing large language models (LLMs) for local deployment in domain-specific use cases is necessary for strong performance while meeting latency and privacy constraints. Howev…