3 papers
cs.LG2025
Enhancing Trustworthiness with Mixed Precision: Benchmarks, Opportunities, and Challenges
Guanxi Lu, Hao Mark Chen, Zhiqiang Que +2
Large language models (LLMs) have shown promising performance across various tasks. However, their autoregressive decoding process poses significant challenges for efficient deploy…
cs.LG2025
FastTTS: Accelerating Test-Time Scaling for Edge LLM Reasoning
Hao Mark Chen, Zhiwen Mo, Guanxi Lu +4
Recent advances in reasoning Large Language Models (LLMs) are driving the emergence of agentic AI systems. Edge deployment of LLM agents near end users is increasingly necessary to…
cs.AI2025
Rethinking Optimal Verification Granularity for Compute-Efficient Test-Time Scaling
Hao Mark Chen, Guanxi Lu, Yasuyuki Okoshi +3
Test-time scaling (TTS) has proven effective in enhancing the reasoning capabilities of large language models (LLMs). Verification plays a key role in TTS, simultaneously influenci…