23 papers
OTCache: Optimal Transport for Geometry-Aware Caching in Diffusion Models
Huanlin Gao, Fang Zhao, Qiang Hui +8
We propose OTCache, a training-free framework for accelerating diffusion sampling via caching schedule prediction. Existing graph-based caching methods reduce redundant computation…
PaLMR: Towards Faithful Visual Reasoning via Multimodal Process Alignment
Yantao Li, Qiang Hui, Chenyang Yan +8
Reinforcement learning has recently improved the reasoning ability of Large Language Models and Multimodal LLMs, yet prevailing reward designs emphasise final-answer correctness an…
Mixture of Heterogeneous Grouped Experts for Language Modeling
Zhicheng Ma, Xiang Liu, Zhaoxiang Liu +5
Large Language Models (LLMs) based on Mixture-of-Experts (MoE) are pivotal in industrial applications for their ability to scale performance efficiently. However, standard MoEs enf…
GLM-5 Serving Parameter Tuning for OpenClaw: Single-Deployment MaaS Inference Optimization for Long-Context Agent Workloads
Minjie Hua, Ning Wang, Peijun Yang +2
OpenClaw requests are dominated by long, tool-augmented prefixes, including system prompts, conversation history, and tool outputs fed back into the context window. For this worklo…
Chain-of-Trajectories: Unlocking the Intrinsic Generative Optimality of Diffusion Models via Graph-Theoretic Planning
Ping Chen, Xiang Liu, Xingpeng Zhang +7
Diffusion models operate in a reflexive System 1 mode, constrained by a fixed, content-agnostic sampling schedule. This rigidity arises from the curse of state dimensionality, wher…
HEAL: Hindsight Entropy-Assisted Learning for Reasoning Distillation
Wenjing Zhang, Jiangze Yan, Jieyun Huang +7
Distilling reasoning capabilities from Large Reasoning Models (LRMs) into smaller models is typically constrained by the limitation of rejection sampling. Standard methods treat th…