4 papers
SearchAuditor: Auditing and Attributing Failures in Long-Horizon Search Agents
Zhixiang Liang, Yifei Liu, Yidan Huang +5
Deep search agents tackle challenging questions through long-horizon web interactions, a process that is both complex and fragile: small reasoning errors may propagate through long…
Quantization Inflates Reasoning: Token Inflation as a Hidden Cost of Low-Bit Reasoning Models
Xinyu Lian, Walid Krichene, Beichen Huang +4
Quantization is widely used to reduce the inference cost of large language models, but its effect on reasoning models is not fully captured by final-answer accuracy or per-token la…
Hidden States as Early Signals: Step-level Trace Evaluation and Pruning for Efficient Test-Time Scaling
Zhixiang Liang, Beichen Huang, Zheng Wang +1
Large Language Models (LLMs) can enhance reasoning capabilities through test-time scaling by generating multiple traces. However, the combination of lengthy reasoning traces with m…
MiLo: Efficient Quantized MoE Inference with Mixture of Low-Rank Compensators
Beichen Huang, Yueming Yuan, Zelei Shao +1
A critical approach for efficiently deploying Mixture-of-Experts (MoE) models with massive parameters is quantization. However, state-of-the-art MoE models suffer from non-negligib…