306 citations · 386 across the 87 of their papers we have counts for
33 papers · 1 filter
Accelerate Speculative Decoding with Sparse Computation in Verification
Jikai Wang, Jianchao Tan, Yuxuan Hu +6
Speculative decoding accelerates autoregressive language model inference by verifying multiple draft tokens in parallel. However, the verification stage often becomes the dominant…
Think Before You Prune: Selective Self-Generated Calibration for Pruning Large Reasoning Models
Yang Xiang, Yixin Ji, Juntao Li +1
Large Reasoning Models (LRMs) have demonstrated remarkable performance on complex reasoning benchmarks. However, their long chain-of-thought reasoning processes incur significant i…
: Attention-Aware Accurate KV Cache Fusion for Fast Large Language Model Serving
Yuechi Zhou, Yi Su, Jianxin Zhang +5
Large language models (LLMs) have demonstrated strong capabilities in processing long contexts, enabling them to tackle tasks involving long textual inputs such as multi-turn conve…
Overview of CHIP 2025 Shared Task 2: Discharge Medication Recommendation for Metabolic Diseases Based on Chinese Electronic Health Records
Juntao Li, Haobin Yuan, Ling Luo +8
Discharge medication recommendation plays a critical role in ensuring treatment continuity, preventing readmission, and improving long-term management for patients with chronic met…
LongRM: Revealing and Unlocking the Context Boundary of Reward Modeling
Zecheng Tang, Baibei Ji, Quantong Qiu +4
Reward model (RM) plays a pivotal role in aligning large language model (LLM) with human preferences. As real-world applications increasingly involve long history trajectories, e.g…
Revisiting Long-context Modeling from Context Denoising Perspective
Zecheng Tang, Baibei Ji, Juntao Li +3
Long-context models (LCMs) have demonstrated great potential in processing long sequences, facilitating many real-world applications. The success of LCMs can be attributed to their…
MMLongCite: A Benchmark for Evaluating Faithfulness of Long-Context Vision-Language Models
Keyan Zhou, Zecheng Tang, Lingfeng Ming +9
The rapid advancement of long-context vision language models (LCVLMs) has led to a significant expansion of their context windows. However, an extended context window does not guar…
SCAN: Self-Denoising Monte Carlo Annotation for Robust Process Reward Learning
Yuyang Ding, Xinyu Shi, Juntao Li +3
Process reward models (PRMs) offer fine-grained, step-level evaluations that facilitate deeper reasoning processes in large language models (LLMs), proving effective in complex tas…
A Unified Biomedical Named Entity Recognition Framework with Large Language Models
Tengxiao Lv, Ling Luo, Juntao Li +9
Accurate recognition of biomedical named entities is critical for medical information extraction and knowledge discovery. However, existing methods often struggle with nested entit…
Benchmarking Chinese Commonsense Reasoning with a Multi-hop Reasoning Perspective
Wangjie You, Xusheng Wang, Xing Wang +4
While Large Language Models (LLMs) have demonstrated advanced reasoning capabilities, their comprehensive evaluation in general Chinese-language contexts remains understudied. To b…
Scaling Code-Assisted Chain-of-Thoughts and Instructions for Model Reasoning
Honglin Lin, Qizhi Pei, Xin Gao +5
Reasoning capability is pivotal for Large Language Models (LLMs) to solve complex tasks, yet achieving reliable and scalable reasoning remains challenging. While Chain-of-Thought (…
FAPO: Flawed-Aware Policy Optimization for Efficient and Reliable Reasoning
Yuyang Ding, Chi Zhang, Juntao Li +2
Reinforcement learning with verifiable rewards (RLVR) has emerged as a promising paradigm for enhancing the reasoning capabilities of large language models (LLMs). In this context,…
MediRec: Enhancing Chinese Medication Recommendation with Explainable Clinical Reasoning
Juntao Li, Haobin Yuan, Ling Luo +3
Large language models (LLMs) have shown strong potential for clinical decision support through their advanced language understanding and reasoning capabilities. However, their appl…
BatonVoice: An Operationalist Framework for Enhancing Controllable Speech Synthesis with Linguistic Intelligence from LLMs
Yue Wang, Ruotian Ma, Xingyu Chen +12
The rise of Large Language Models (LLMs) is reshaping multimodel models, with speech synthesis being a prominent application. However, existing approaches often underutilize the li…
Learning Active Perception via Self-Evolving Preference Optimization for GUI Grounding
Wanfu Wang, Qipeng Huang, Guangquan Xue +2
Vision Language Models (VLMs) have recently achieved significant progress in bridging visual perception and linguistic reasoning. Recently, OpenAI o3 model introduced a zoom-in sea…
CaliDrop: KV Cache Compression with Calibration
Yi Su, Quantong Qiu, Yuechi Zhou +6
Large Language Models (LLMs) require substantial computational resources during generation. While the Key-Value (KV) cache significantly accelerates this process by storing attenti…
LOOM-Scope: a comprehensive and efficient LOng-cOntext Model evaluation framework
Zecheng Tang, Haitian Wang, Quantong Qiu +5
Long-context processing has become a fundamental capability for large language models~(LLMs). To assess model's long-context performance, numerous long-context evaluation benchmark…
Improving Rationality in the Reasoning Process of Language Models through Self-playing Game
Pinzheng Wang, Juntao Li, Zecheng Tang +2
Large language models (LLMs) have demonstrated considerable reasoning abilities in various tasks such as mathematics and coding. However, recent studies indicate that even the best…
Unlocking Recursive Thinking of LLMs: Alignment via Refinement
Haoke Zhang, Xiaobo Liang, Cunxiang Wang +2
The OpenAI o1-series models have demonstrated that leveraging long-form Chain of Thought (CoT) can substantially enhance performance. However, the recursive thinking capabilities o…
Efficient Reasoning for LLMs through Speculative Chain-of-Thought
Jikai Wang, Juntao Li, Jianye Hou +3
Large reasoning language models such as OpenAI-o1 and Deepseek-R1 have recently attracted widespread attention due to their impressive task-solving abilities. However, the enormous…
Towards DS-NER: Unveiling and Addressing Latent Noise in Distant Annotations
Yuyang Ding, Dan Qiao, Juntao Li +4
Distantly supervised named entity recognition (DS-NER) has emerged as a cheap and convenient alternative to traditional human annotation methods, enabling the automatic generation…
Accurate KV Cache Quantization with Outlier Tokens Tracing
Yi Su, Yuechi Zhou, Quantong Qiu +6
The impressive capabilities of Large Language Models (LLMs) come at the cost of substantial computational resources during deployment. While KV Cache can significantly reduce recom…
Alignment-Augmented Speculative Decoding with Alignment Sampling and Conditional Verification
Jikai Wang, Zhenxu Tian, Juntao Li +5
Recent works have revealed the great potential of speculative decoding in accelerating the autoregressive generation process of large language models. The success of these methods…
OpenThinkIMG: Learning to Think with Images via Visual Tool Reinforcement Learning
Zhaochen Su, Linjie Li, Mingyang Song +8
While humans can flexibly leverage interactive visual cognition for complex problem-solving, enabling Large Vision-Language Models (LVLMs) to learn similarly adaptive behaviors wit…