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cs.CL2026

Optimizing Denoising Trajectories in dLLMs: A Lightweight Evolutionary Heuristic Approach

Zijian Zhao, Dian Jin, Xialiang Tong +2

Diffusion Large Language Models (dLLMs) have recently emerged as a promising alternative to conventional Auto-Regressive (AR) Large Language Models (LLMs). By leveraging bidirectio…

cs.CL2026

DLLM Agent: See Farther, Run Faster

Huiling Zhen, Weizhe Lin, Renxi Liu +15

Diffusion large language models (DLLMs) have emerged as an alternative to autoregressive (AR) decoding with appealing efficiency and modeling properties, yet their implications for…

cs.CL2026

From Conflict to Consensus: Boosting Medical Reasoning via Multi-Round Agentic RAG

Wenhao Wu, Zhentao Tang, Yafu Li +5

Large Language Models (LLMs) exhibit high reasoning capacity in medical question-answering, but their tendency to produce hallucinations and outdated knowledge poses critical risks…

cs.CL2026

Unleashing Low-Bit Inference on Ascend NPUs: A Comprehensive Evaluation of HiFloat Formats

Pengxiang Zhao, Hui-Ling Zhen, Xing Li +10

As LLMs scale, low-bit floating-point formats like MXFP and NVFP4 offer new opportunities for precision and efficiency. In this work, we evaluate HiFloat (HiF8 and HiF4), a family…

cs.CL2026

C-MOP: Integrating Momentum and Boundary-Aware Clustering for Enhanced Prompt Evolution

Binwei Yan, Yifei Fu, Mingjian Zhu +4

Automatic prompt optimization is a promising direction to boost the performance of Large Language Models (LLMs). However, existing methods often suffer from noisy and conflicting u…

cs.CL2026

Why Attention Patterns Exist: A Unifying Temporal Perspective Analysis

Qingyue Yang, Jie Wang, Xing Li +6

Attention patterns play a crucial role in both training and inference of large language models (LLMs). Prior works have identified individual patterns such as retrieval heads, sink…

cs.CL2026

Beyond Speedup -- Utilizing KV Cache for Sampling and Reasoning

Zeyu Xing, Xing Li, Hui-Ling Zhen +2

KV caches, typically used only to speed up autoregressive decoding, encode contextual information that can be reused for downstream tasks at no extra cost. We propose treating the…

cs.CL2025

Towards Efficient Agents: A Co-Design of Inference Architecture and System

Weizhe Lin, Hui-Ling Zhen, Shuai Yang +14

The rapid development of large language model (LLM)-based agents has unlocked new possibilities for autonomous multi-turn reasoning and tool-augmented decision-making. However, the…

cs.CL2025

AttentionPredictor: Temporal Patterns Matter for KV Cache Compression

Qingyue Yang, Jie Wang, Xing Li +8

With the development of large language models (LLMs), efficient inference through Key-Value (KV) cache compression has attracted considerable attention, especially for long-context…