Jingrui He
Jingrui He has 6 papers in our library, in 2026, most of them on Language models & pretraining, Vision & language, Dialogue systems; often with Hanghang Tong, Tianxin Wei, Xuying Ning.
OpenAlex · h-index 5 · 14 works · 63 citations OpenAlex, 2026-10-14
📄 6 works in our library · 🔗 Cited 14 times in our library · ⭐ Paper Stars ranking: #10635
Affiliations
Fields, topics and concepts
📚 Shelves 7The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 6 worksComputer Science · 6 worksArtificial Intelligence · 6 worksLanguage and Linguistics · 6 worksComputer Vision and Pattern Recognition · 3 worksInformation Systems · 3 worksHistory and Philosophy of Science · 1 work
🧭 Topics 6Research subjects and languages the work is about.Vision & language · 2 worksInformation retrieval & search · 1 workLanguage models & pretraining · 2 worksEfficient models & compression · 1 workDialogue systems · 1 workReasoning · 1 work
Works by year
2020s
Papers
- Mem-Gallery: Benchmarking Multimodal Long-Term Conversational Memory for MLLM Agents (2026 · 6 citations)
Agents built on multimodal large language models (MLLMs) need to remember what users show and tell them over many conversations. - RAG over Tables: Hierarchical Memory Index, Multi-Stage Retrieval, and Benchmarking (2026 · 3 citations)
Many real questions can only be answered by combining facts spread over several tables, yet RAG systems mostly target plain text, and realistic benchmarks for multi-table retrieval are scarce. - Harnessing Consistency for Robust Test-Time LLM Ensemble (2026 · 2 citations)
Test-time ensembles of large language models aim to combine the complementary strengths of different LLMs. - PAPERMIND: Benchmarking Agentic Reasoning and Critique over Scientific Papers in Multimodal LLMs (2026 · 2 citations)
PaperMind is a benchmark for testing whether multimodal LLMs can reason about scientific papers in an integrated, agent-like way. - Prune as You Generate: Online Rollout Pruning for Faster and Better RLVR (2026 · 2 citations)
RLVR methods such as GRPO and DAPO are expensive because they sample many rollouts per prompt. Their learning signal is also often weak: when a group's rewards are almost all correct or almost all wrong, group-normalized advantages approach zero. The authors propose ARRoL (Accelerating RLVR via online RoLlout… - Copyright Detective: A Forensic System to Evidence LLMs Flickering Copyright Leakage Risks (2026)
Copyright Detective is an interactive forensic tool for collecting evidence that LLMs may reproduce copyrighted material.
Co-authors here
- Hanghang Tong ×4
- Tianxin Wei ×3
- Xuying Ning ×3
- Jiaru Zou ×2
- Ruizhong Qiu ×2
- Sirui Chen ×2
- Xiao Lin ×2
- Yada Zhu ×2
- Yanjun Zhao ×2
- Yuanchen Bei ×2
- Yuchen Yan ×2
- Ahmed Abbasi
Venues
- Annual Meeting of the Association for Computational Linguistics (ACL) ×3: ACL 2026 ×3
- Findings of the Association for Computational Linguistics ×3: Findings of the Association for Computational Linguistics 2026 ×3
Cited by
Updated
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