127 citations · 190 across the 8 of their papers we have counts for
8 papers
Confidence Before Answering: A Paradigm Shift for Efficient LLM Uncertainty Estimation
Changcheng Li, Jiancan Wu, Hengheng Zhang +5
Reliable deployment of large language models (LLMs) requires accurate uncertainty estimation. Existing methods are predominantly answer-first, producing confidence only after gener…
Punctuation-aware Hybrid Trainable Sparse Attention for Large Language Models
Junxiang Qiu, Shuo Wang, Zhengsu Chen +4
Attention serves as the fundamental mechanism for long-context modeling in large language models (LLMs), yet dense attention becomes structurally prohibitive for long sequences due…
Beyond Empathy: Integrating Diagnostic and Therapeutic Reasoning with Large Language Models for Mental Health Counseling
He Hu, Yucheng Zhou, Juzheng Si +6
Large language models (LLMs) hold significant potential for mental health support, capable of generating empathetic responses and simulating therapeutic conversations. However, exi…
QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models
Yuhui Xu, Lingxi Xie, Xiaotao Gu +6
Recently years have witnessed a rapid development of large language models (LLMs). Despite the strong ability in many language-understanding tasks, the heavy computational burden l…
Pipeline MoE: A Flexible MoE Implementation with Pipeline Parallelism
Xin Chen, Hengheng Zhang, Xiaotao Gu +3
The Mixture of Experts (MoE) model becomes an important choice of large language models nowadays because of its scalability with sublinear computational complexity for training and…
Pangu-Weather: A 3D High-Resolution Model for Fast and Accurate Global Weather Forecast
Kaifeng Bi, Lingxi Xie, Hengheng Zhang +3
In this paper, we present Pangu-Weather, a deep learning based system for fast and accurate global weather forecast. For this purpose, we establish a data-driven environment by dow…
Rethinking the Distribution Gap of Person Re-identification with Camera-based Batch Normalization
Zijie Zhuang, Longhui Wei, Lingxi Xie +5
The fundamental difficulty in person re-identification (ReID) lies in learning the correspondence among individual cameras. It strongly demands costly inter-camera annotations, yet…
Person Re-identification in the Wild
Liang Zheng, Hengheng Zhang, Shaoyan Sun +3
We present a novel large-scale dataset and comprehensive baselines for end-to-end pedestrian detection and person recognition in raw video frames. Our baselines address three issue…