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researcher

Yizhi Li

University of Manchester

50 papers hereh-index 251.9k citations57 works total

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

author position
  • first author7
  • middle author32

Across the 39 of 50 papers where every author was matched, so the position is known.

fields
  • cs.CL24
  • cs.SD9
  • cs.AI4
  • cs.CV3
  • cs.IR3
  • cs.LG2
affiliations
  • University of Manchester
ORCID 0000-0002-3932-9706
same name
  • Yizhi Li — 8 papers, h 3
  • Yizhi Li — 4 papers, h 2
  • Yizhi Li — 3 papers, h 2
  • Yizhi Li — 3 papers, h 2
  • Yizhi Li — 2 papers, h 3
  • Yizhi LI — 1 paper

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
20212026
most citedMERT: Acoustic Music Understanding Model with Large-Scale Self-supervised Training

28 citations · 128 across the 48 of their papers we have counts for

collaborators
Showing cs.AIShow all

4 papers · 1 filter

cs.AI2026

CoTJudger: A Graph-Driven Framework for Automatic Evaluation of Chain-of-Thought Efficiency and Redundancy in LRMs

Siyi Li, Jiajun Shi, Shiwen Ni +9

Large Reasoning Models (LRMs) have demonstrated strong performance by producing extended Chain-of-Thought (CoT) traces before answering. However, this paradigm often induces over-r…

cs.AI2025

OmniVideoBench: Towards Audio-Visual Understanding Evaluation for Omni MLLMs

Caorui Li, Yu Chen, Yiyan Ji +40

Recent advances in multimodal large language models (MLLMs) have demonstrated substantial potential in video understanding. However, existing benchmarks fail to comprehensively eva…

cs.AI2025

First Return, Entropy-Eliciting Explore

Tianyu Zheng, Tianshun Xing, Qingshui Gu +10

Reinforcement Learning from Verifiable Rewards (RLVR) improves the reasoning abilities of Large Language Models (LLMs) but it struggles with unstable exploration. We propose FR3E (…

cs.AI2022★ 1 cited

TranSHER: Translating Knowledge Graph Embedding with Hyper-Ellipsoidal Restriction

Yizhi Li, Wei Fan, Chao Liu +2

Knowledge graph embedding methods are important for the knowledge graph completion (or link prediction) task. One existing efficient method, PairRE, leverages two separate vectors…

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