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Junlin Liu

16 papers hereh-index 6393 citations24 works total

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

author position
  • sole author1
  • first author1
  • middle author13

Across the 15 of 16 papers where every author was matched, so the position is known.

fields
  • cs.LG7
  • cs.AI3
  • cs.CL3
  • cs.CE1
  • cs.RO1
  • cs.SE1
same name
  • Junlin Liu — 3 papers, h 2
  • Junlin Liu — 2 papers, h 4
  • Junlin Liu — 1 paper, h 0
  • Junlin Liu — 1 paper, h 0

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

works on
large language models 3autonomous agents 1benchmarking 1co-evolution 1context compression 1contrastive learning 1kv cache 1long-context inference 1long-horizon reasoning 1memory selection 1model efficiency 1multi-step reasoning 1

From the 4 of 16 linked papers with an AI index.

activity
20242026
collaborators
Showing cs.AIShow all

3 papers · 1 filter

cs.AI2026

PCSD: Persistent Consistency for Self-Distillation in Agentic Reinforcement Learning

Chunji Lv, Yangguang Wei, Junlin Liu +6

Large language model agents have shown strong potential in complex interactive tasks, yet their reinforcement learning (RL) is often hindered by sparse rewards, as a long multi-tur…

cs.AI2026

DecoEvo: Score-Decoupled Co-Evolution of Solver and Rubric-Generator Skills in Text Space

Jiangwang Chen, Zixin Song, Junlin Liu +10

The paper introduces DecoEvo, a method that co-evolves a solver and a rubric-generator for large language models in text space using decoupled objectives, allowing the solver to im…

cs.AI2026

From Proprietary to Open-Source: Bridging the Distribution Gap via Multi-Agent Protocol Distillation in Agentic Search

Junlin Liu, Jiangwang Chen, Zixin Song +7

Agentic search enables large language models to solve knowledge-intensive tasks by interleaving multi-step reasoning with retrieval, yet optimizing this with outcome-based reinforc…

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