7 papers
Model Guides You How to Draw: Adaptive Visual Gating for Unified Multimodal Reasoning
Wenxi Gao, Guanxi Lu, Didi Zhu +5
Unified multimodal models (UMMs) with interleaved reasoning, which generate both textual and visual steps as part of intermediate reasoning traces, have demonstrated great potentia…
CLORE: Content-Level Optimization for Reasoning Efficiency
Yuyang Wu, Qiyao Xue, Guanxing Lu +4
Reinforcement learning post-training has improved the reasoning ability of large language models, but often produces unnecessarily long, repetitive, or semantically opaque reasonin…
Context Memorization for Efficient Long Context Generation
Yasuyuki Okoshi, Hao Mark Chen, Guanxi Lu +3
Modern large language model (LLM) applications increasingly rely on long conditioning prefixes to control model behavior at inference time. While prefix-augmented inference is effe…
AdaBlock-dLLM: Semantic-Aware Diffusion LLM Inference via Adaptive Block Size
Guanxi Lu, Hao Mark Chen, Yuto Karashima +3
Diffusion-based large language models (dLLMs) are gaining attention for their inherent capacity for parallel decoding, offering a compelling alternative to autoregressive LLMs. Amo…
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…
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…