11 citations · 27 across the 50 of their papers we have counts for
9 papers · 1 filter
LouisKV: Efficient KV Cache Retrieval for Long Input-Output Sequences
Wenbo Wu, Qingyi Si, Xiurui Pan +2
While Key-Value (KV) cache succeeds in reducing redundant computations in auto-regressive models, it introduces significant memory overhead, limiting its practical deployment in lo…
HANDO: Hierarchical Autonomous Navigation and Dexterous Omni-loco-manipulation
Jingyuan Sun, Chaoran Wang, Mingyu Zhang +6
Seamless loco-manipulation in unstructured environments requires robots to leverage autonomous exploration alongside whole-body control for physical interaction. In this work, we i…
Breaking the Trade-Off Between Faithfulness and Expressiveness for Large Language Models
Chenxu Yang, Qingyi Si, Zheng Lin
Grounding responses in external knowledge represents an effective strategy for mitigating hallucinations in Large Language Models (LLMs). However, current LLMs struggle to seamless…
Sparse Attention across Multiple-context KV Cache
Ziyi Cao, Qingyi Si, Jingbin Zhang +1
Large language models face significant cost challenges in long-sequence inference. To address this, reusing historical Key-Value (KV) Cache for improved inference efficiency has be…
Test-time Prompt Intervention
Chenxu Yang, Qingyi Si, Mz Dai +5
Test-time compute has led to remarkable success in the large language model (LLM) community, particularly for complex tasks, where longer chains of thought (CoTs) are generated to…
Stable Reinforcement Learning for Efficient Reasoning
Muzhi Dai, Shixuan Liu, Qingyi Si
The success of Deepseek-R1 has drawn the LLM community's attention to reinforcement learning (RL) methods like GRPO. However, such rule-based 0/1 outcome reward methods lack the ca…
S-GRPO: Early Exit via Reinforcement Learning in Reasoning Models
Muzhi Dai, Chenxu Yang, Qingyi Si
As Test-Time Scaling emerges as an active research focus in the large language model community, advanced post-training methods increasingly emphasize extending chain-of-thought (Co…
Dynamic Early Exit in Reasoning Models
Chenxu Yang, Qingyi Si, Yongjie Duan +6
Recent advances in large reasoning language models (LRLMs) rely on test-time scaling, which extends long chain-of-thought (CoT) generation to solve complex tasks. However, overthin…
AdaReTaKe: Adaptive Redundancy Reduction to Perceive Longer for Video-language Understanding
Xiao Wang, Qingyi Si, Jianlong Wu +3
Multimodal Large Language Models (MLLMs) have revolutionized video understanding, yet are still limited by context length when processing long videos. Recent methods compress video…