1 citations · 2 across the 13 of their papers we have counts for
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GeoFaith: A Spatio-Temporal Dual View of Faithful Chain-of-Thought
Weijiang Lv, Wentong Zhao, Jiayu Wang +3
Chain-of-Thought (CoT) reasoning has advanced large language models (LLMs), but outcome-based supervision leads to pervasive post-hoc rationalization, producing plausible yet unfai…
QuantClaw: Precision Where It Matters for OpenClaw
Manyi Zhang, Ji-Fu Li, Zhongao Sun +5
Autonomous agent systems such as OpenClaw introduce significant efficiency challenges due to long-context inputs and multi-turn reasoning. This results in prohibitively high comput…
BATQuant: Outlier-resilient MXFP4 Quantization via Learnable Block-wise Optimization
Ji-Fu Li, Manyi Zhang, Xiaobo Xia +4
Microscaling floating-point (MXFP) formats have emerged as a promising standard for deploying Multi-modal Large Language Models (MLLMs) and Large Language Models (LLMs) on modern a…
SPD-Faith Bench: Diagnosing and Improving Faithfulness in Chain-of-Thought for Multimodal Large Language Models
Weijiang Lv, Yaoxuan Feng, Xiaobo Xia +4
Chain-of-Thought reasoning is widely used to improve the interpretability of multimodal large language models (MLLMs), yet the faithfulness of the generated reasoning traces remain…
What Makes Low-Bit Quantization-Aware Training Work for Reasoning LLMs? A Systematic Study
Keyu Lv, Manyi Zhang, Xiaobo Xia +6
Reasoning models excel at complex tasks such as coding and mathematics, yet their inference is often slow and token-inefficient. To improve the inference efficiency, post-training…