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Jie Li

15 papers hereh-index 568 citations31 works total

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

author position
  • middle author4
  • last author10

Across the 14 of 15 papers where every author was matched, so the position is known.

fields
  • cs.AI4
  • cs.LG4
  • cs.DC2
  • cs.CL1
  • cs.CV1
  • cs.CY1
same name
  • Jie Li — 41 papers, h 46
  • Jie Li — 39 papers, h 35
  • Jie Li — 39 papers, h 21
  • Jie Li — 38 papers, h 14
  • Jie Li — 27 papers, h 50
  • Jie Li — 21 papers, h 16

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
20232026
most citedRobust and Communication-Efficient Federated Domain Adaptation via Random Features

3 citations · 3 across the 11 of their papers we have counts for

collaborators
Showing cs.AIShow all

4 papers · 1 filter

cs.AI2026

Learning from Unverified Peers via Shared Residual Distillation

Feiyang Chen, Runze Ma, Zichen Wang +4

A language model can generate several solutions to the same problem, some leading to correct answers and others to incorrect ones. Many post-training methods turn these trajectorie…

cs.AI2026

Jev-LiteMAS: Separating Decisions from Generation in Multi-Agent Workflows

Kaixiang Wang, Zhaijiacheng Zhou, Jiong Lou +1

Multi-agent LLM systems rely on generative models for expert execution, workflow planning, and artifact review. Yet many coordination operations require only bounded decisions, suc…

cs.AI2026

GateSight: Recurrent Memory Anticipates Attention Memory for Query-Agnostic KV Eviction in Hybrid LLMs

Junjie Li, Jiong Lou, Jie Li

Hybrid language models interleave Gated DeltaNet (GDN) layers, whose recurrent memory has a fixed size, with full-attention layers, whose key-value (KV) cache grows with the contex…

cs.AI2026

Deep Interaction: An Efficient Human-AI Interaction Method for Large Reasoning Models

Hefeng Zhou, Jinxuan Zhang, Jiong Lou +4

The emergence of Chain-of-Thought (CoT) reasoning has significantly enhanced the ability of large language models (LLMs) to tackle complex, multi-step tasks. However, when errors o…

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