48 citations · 57 across the 7 of their papers we have counts for
8 papers
Beyond Fast and Slow: Cognitive-Inspired Elastic Reasoning for Large Language Models
Jinwu Hu, Dongjin Yang, Langyu Bian +6
Large language models (LLMs) have demonstrated impressive performance across various language tasks. However, existing LLM reasoning strategies mainly rely on the LLM itself with f…
Test-Time Learning for Large Language Models
Jinwu Hu, Zhitian Zhang, Guohao Chen +6
While Large Language Models (LLMs) have exhibited remarkable emergent capabilities through extensive pre-training, they still face critical limitations in generalizing to specializ…
Curse of High Dimensionality Issue in Transformer for Long-context Modeling
Shuhai Zhang, Zeng You, Yaofo Chen +5
Transformer-based large language models (LLMs) excel in natural language processing tasks by capturing long-range dependencies through self-attention mechanisms. However, long-cont…
Detecting Machine-Generated Texts by Multi-Population Aware Optimization for Maximum Mean Discrepancy
Shuhai Zhang, Yiliao Song, Jiahao Yang +3
Large language models (LLMs) such as ChatGPT have exhibited remarkable performance in generating human-like texts. However, machine-generated texts (MGTs) may carry critical risks,…
V2C: Visual Voice Cloning
Qi Chen, Yuanqing Li, Yuankai Qi +3
Existing Voice Cloning (VC) tasks aim to convert a paragraph text to a speech with desired voice specified by a reference audio. This has significantly boosted the development of a…
Rapid Elastic Architecture Search under Specialized Classes and Resource Constraints
Jing Liu, Bohan Zhuang, Mingkui Tan +4
In many real-world applications, we often need to handle various deployment scenarios, where the resource constraint and the superclass of interest corresponding to a group of clas…
EPMF: Efficient Perception-aware Multi-sensor Fusion for 3D Semantic Segmentation
Mingkui Tan, Zhuangwei Zhuang, Sitao Chen +4
We study multi-sensor fusion for 3D semantic segmentation that is important to scene understanding for many applications, such as autonomous driving and robotics. Existing fusion-b…
DualPoseNet: Category-level 6D Object Pose and Size Estimation Using Dual Pose Network with Refined Learning of Pose Consistency
Jiehong Lin, Zewei Wei, Zhihao Li +3
Category-level 6D object pose and size estimation is to predict full pose configurations of rotation, translation, and size for object instances observed in single, arbitrary views…