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Tat-Seng Chua

22 papers hereh-index 8169 citations20 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2
  • last author18

Across the 20 of 22 papers where every author was matched, so the position is known.

fields
  • cs.CV13
  • cs.CL4
  • cs.LG4
  • cs.RO1
same name
  • Tat-seng Chua — 98 papers, h 55
  • Tat-Seng Chua — 89 papers, h 113
  • Tat-Seng Chua — 74 papers, h 31
  • Tat-Seng Chua — 74 papers, h 22
  • Tat-Seng Chua — 30 papers, h 3
  • Tat-Seng Chua — 27 papers, h 10

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20242026
collaborators
Showing cs.CLShow all

4 papers · 1 filter

cs.CL2026

FreeAct: Freeing Activations for LLM Quantization

Xiaohao Liu, Xiaobo Xia, Manyi Zhang +6

Quantization is pivotal for mitigating the significant memory and computational overhead of Large Language Models (LLMs). While emerging transformation-based methods have successfu…

cs.CL2025

NExT-OMNI: Towards Any-to-Any Omnimodal Foundation Models with Discrete Flow Matching

Run Luo, Xiaobo Xia, Lu Wang +5

Next-generation multimodal foundation models capable of any-to-any cross-modal generation and multi-turn interaction will serve as core components of artificial general intelligenc…

cs.CL2025

L-MTP: Leap Multi-Token Prediction Beyond Adjacent Context for Large Language Models

Xiaohao Liu, Xiaobo Xia, Weixiang Zhao +6

Large language models (LLMs) have achieved notable progress. Despite their success, next-token prediction (NTP), the dominant method for LLM training and inference, is constrained…

cs.CL2025

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization

Zhenglin Zhou, Xiaobo Xia, Fan Ma +3

Text-to-3D generation automates 3D content creation from textual descriptions, which offers transformative potential across various fields. However, existing methods often struggle…

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