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Tong Zhao

9 papers hereh-index 568 citations16 works total

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

author position
  • middle author3
  • last author6

Across the 9 of 9 papers where every author was matched, so the position is known.

fields
  • cs.IR4
  • cs.LG4
  • cs.CL1
same name
  • Tong Zhao — 21 papers, h 22
  • Tong Zhao — 19 papers, h 12
  • Tong Zhao — 17 papers, h 6
  • Tong Zhao — 13 papers, h 4
  • Tong Zhao — 10 papers, h 1
  • Tong Zhao — 9 papers, h 8

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.LGShow all

4 papers · 1 filter

cs.LG2026

Threshold Differential Attention for Sink-Free, Ultra-Sparse, and Non-Dispersive Language Modeling

Xingyue Huang, Xueying Ding, Mingxuan Ju +3

Softmax attention struggles with long contexts due to structural limitations: the strict sum-to-one constraint forces attention sinks on irrelevant tokens, and probability mass dis…

cs.LG2025

Learning Along the Arrow of Time: Hyperbolic Geometry for Backward-Compatible Representation Learning

Ngoc Bui, Menglin Yang, Runjin Chen +5

Backward compatible representation learning enables updated models to integrate seamlessly with existing ones, avoiding to reprocess stored data. Despite recent advances, existing…

cs.LG2025

Heuristic Methods are Good Teachers to Distill MLPs for Graph Link Prediction

Zongyue Qin, Shichang Zhang, Mingxuan Ju +3

Link prediction is a crucial graph-learning task with applications including citation prediction and product recommendation. Distilling Graph Neural Networks (GNNs) teachers into M…

cs.LG2024

Enhancing Item Tokenization for Generative Recommendation through Self-Improvement

Runjin Chen, Mingxuan Ju, Ngoc Bui +7

Generative recommendation systems, driven by large language models (LLMs), present an innovative approach to predicting user preferences by modeling items as token sequences and ge…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.