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Showing papers from Shanghai Innovation Institute Show all papers

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arXivU Science and Technology of Chin Shanghai Innovation Institute Fudan Shanghai Artificial Intelligence LLM agents & planning

GraphForge: Training Working Agents with Graph-Anchored Workspace Synthesis

GraphForge synthesizes workspace tasks and verifiers over real file evidence graphs to train working agents, and fine-tuning Qwen3.6-27B improves GDPVal, Workspace-Bench-Lite, and SpreadsheetBench II results.

Qisheng Su, Hanchen Wang, 朱冠儒, Huicheng Jiang and 8 more

Published Sep 30, 2026 · 0 citations · ▲ 146 on Hugging Face

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15/20 AI panelreviewers recommend it

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AI panel: 15 of 20 reviewers recommend it

lenient 5/5

medium 9/10

strict 1/5

91%Must read

arXivShanghai Jiao Tong Fudan Shanghai Innovation Institute Northeastern LLM reasoning & chain of thought

Does Learning Protein Folding Generalize to Broader Reasoning?

Post-training on protein-folding data via discrete answers and continuous geometry improves structure prediction and broad reasoning across ten benchmarks.

Yong Liu, Zhanpeng Shi, Yizhou Dang, Zhongyue Zhang and 3 more

Published Sep 30, 2026 · 0 citations · ▲ 120 on Hugging Face · Code ★ 28

100% Readers1 of 1 upvoted

16/20 AI panelreviewers recommend it

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AI panel: 16 of 20 reviewers recommend it

lenient 5/5

medium 9/10

strict 2/5

86%Must read

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arXivEast China Normal Shanghai Innovation Institute Fudan Renmin University of China Tool use & function calling

WEFT: Scaling Tool-Use Post-Training for General-Purpose Agents

WEFT evolves whole agentic interaction systems for tool-use post-training, outperforming environment-scaling baselines by up to 12.27 points across benchmarks.

Bo Mao, Hang He, Linting Wang, Lizhi Lin and 16 more

Published Sep 29, 2026 · 0 citations · ▲ 19 on Hugging Face

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14/20 AI panelreviewers recommend it

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AI panel: 14 of 20 reviewers recommend it

lenient 4/5

medium 8/10

strict 2/5

74%Highly rated

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arXivShanghai Jiao Tong Shanghai Innovation Institute Multi-agent LLM systems

ARIS: Autonomous Research via Adversarial Multi-Agent Collaboration

ARIS is an open-source autonomous research harness using cross-model adversarial collaboration to coordinate ML workflows and verify experimental claims.

Ruofeng Yang, Yongcan Li, Shuai Li

Published May 4, 2026 · 1 citation · ▲ 154 on Hugging Face · Code ★ 17,051

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9/20 AI panelreviewers recommend it

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AI panel: 9 of 20 reviewers recommend it

lenient 5/5

medium 4/10

strict 0/5

76%Highly rated

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arXivFudan Shanghai Innovation Institute Central South Tsinghua RL for LLMs

AI Can Learn Scientific Taste

RLCF trains AI to judge and propose high-impact research ideas via community feedback, showing learned scientific taste generalizes across fields and time.

Jingqi Tong, Mingzhe Li, Hangcheng Li, Yongzhuo Yang and 19 more

Published Mar 15, 2026 · 0 citations · ▲ 316 on Hugging Face · Code ★ 433

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10/20 AI panelreviewers recommend it

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AI panel: 10 of 20 reviewers recommend it

lenient 5/5

medium 4/10

strict 1/5

57%Worth a look

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