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Yang Li

5 papers hereh-index 41.5k citations7 works total

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

author position
  • middle author1

Across the 1 of 5 papers where every author was matched, so the position is known.

fields
  • cs.CL3
  • cs.AI1
  • cs.CV1
same name
  • Yang Li — 24 papers, h 10
  • Yang Li — 17 papers, h 3
  • Yang Li — 12 papers, h 5
  • Yang Li — 12 papers, h 8
  • Yang Li — 9 papers, h 2
  • Yang Li — 9 papers, h 4

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

collaborators

5 papers

cs.CL2026

Kimi K3: Open Frontier Intelligence

Kimi Team, Tongtong Bai, Yifan Bai +398

We introduce Kimi K3, a 2.8T parameter Mixture-of-Experts model with 104 billion activated parameters, native vision capabilities, and a 1-million-token context window. Kimi K3 is…

cs.CL2026

Kimi K2.5: Visual Agentic Intelligence

Kimi Team, Tongtong Bai, Yifan Bai +339

We introduce Kimi K2.5, an open-source multimodal agentic model designed to advance general agentic intelligence. K2.5 emphasizes the joint optimization of text and vision so that…

cs.CL2025

UXAgent: A System for Simulating Usability Testing of Web Design with LLM Agents

Yuxuan Lu, Bingsheng Yao, Hansu Gu +7

Usability testing is a fundamental research method that user experience (UX) researchers use to evaluate and iterate their new designs. But what about evaluating and iterating the…

cs.CV2025

Kimi-VL Technical Report

Kimi Team, Angang Du, Bohong Yin +92

We present Kimi-VL, an efficient open-source Mixture-of-Experts (MoE) vision-language model (VLM) that offers advanced multimodal reasoning, long-context understanding, and strong…

cs.AI2025

Kimi k1.5: Scaling Reinforcement Learning with LLMs

Kimi Team, Angang Du, Bofei Gao +93

Language model pretraining with next token prediction has proved effective for scaling compute but is limited to the amount of available training data. Scaling reinforcement learni…

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