activity
20202025
most citedImproved deep learning techniques in gravitational-wave data analysis

38 citations · 50 across the 12 of their papers we have counts for

collaborators

12 papers

cs.CV2025

SpecVLM: Enhancing Speculative Decoding of Video LLMs via Verifier-Guided Token Pruning

Yicheng Ji, Jun Zhang, Heming Xia +4

Video large language models (Vid-LLMs) have shown strong capabilities in understanding video content. However, their reliance on dense video token representations introduces substa…

cs.CL2025

Towards Harmonized Uncertainty Estimation for Large Language Models

Rui Li, Jing Long, Muge Qi +4

To facilitate robust and trustworthy deployment of large language models (LLMs), it is essential to quantify the reliability of their generations through uncertainty estimation. Wh…

cs.CL2024

Taking a Deep Breath: Enhancing Language Modeling of Large Language Models with Sentinel Tokens

Weiyao Luo, Suncong Zheng, Heming Xia +5

Large language models (LLMs) have shown promising efficacy across various tasks, becoming powerful tools in numerous aspects of human life. However, Transformer-based LLMs suffer a…

cs.CL2024★ 1 cited

Can Large Multimodal Models Uncover Deep Semantics Behind Images?

Yixin Yang, Zheng Li, Qingxiu Dong +2

Understanding the deep semantics of images is essential in the era dominated by social media. However, current research works primarily on the superficial description of images, re…

cs.CL2024★ 1 cited

Unlocking Efficiency in Large Language Model Inference: A Comprehensive Survey of Speculative Decoding

Heming Xia, Zhe Yang, Qingxiu Dong +6

To mitigate the high inference latency stemming from autoregressive decoding in Large Language Models (LLMs), Speculative Decoding has emerged as a novel decoding paradigm for LLM…

cs.CL2023★ 1 cited

Enhancing Continual Relation Extraction via Classifier Decomposition

Heming Xia, Peiyi Wang, Tianyu Liu +3

Continual relation extraction (CRE) models aim at handling emerging new relations while avoiding catastrophically forgetting old ones in the streaming data. Though improvements hav…