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20242026
most citedA Survey on LoRA of Large Language Models

118 citations · 137 across the 17 of their papers we have counts for

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6 papers · 1 filter

cs.IR2026

Stellar: Scalable Multimodal Document Retrieval for Natural Language Queries

Yuxiang Guo, Zhonghao Hu, Yuren Mao +5

Multimodal document retrieval--selecting the most relevant multimodal document from a large corpus to answer a natural language query--plays an essential role in Retrieval-Augmente…

cs.DB2026

LASER: A Data-Centric Method for Low-Cost and Efficient SQL Rewriting based on SQL-GRPO

Jiahui Li, Tongwang Wu, Yuren Mao +3

Query rewriting, the process of transforming queries into semantically equivalent yet more efficient variants, is crucial for database optimization. Existing solutions predominantl…

cs.IR2026

Unbiased Multimodal Reranking for Long-Tail Short-Video Search

Wenyi Xu, Feiran Zhu, Songyang Li +6

Kuaishou serving hundreds of millions of searches daily, the quality of short-video search is paramount. However, it suffers from a severe Matthew effect on long-tail queries: spar…

cs.AI2026

OpenHospital: A Thing-in-itself Arena for Evolving and Benchmarking LLM-based Collective Intelligence

Peigen Liu, Rui Ding, Yuren Mao +7

Large Language Model (LLM)-based Collective Intelligence (CI) presents a promising approach to overcoming the data wall and continuously boosting the capabilities of LLM agents. Ho…

cs.DB2026★ 1 cited

DTBench: A Synthetic Benchmark for Document-to-Table Extraction

Yuxiang Guo, Zhuoran Du, Nan Tang +3

Document-to-table (Doc2Table) extraction derives structured tables from unstructured documents under a target schema, enabling reliable and verifiable SQL-based data analytics. Alt…

cs.CL2026

Can We Predict Before Executing Machine Learning Agents?

Jingsheng Zheng, Jintian Zhang, Yujie Luo +5

Autonomous machine learning agents have revolutionized scientific discovery, yet they remain constrained by a Generate-Execute-Feedback paradigm. Previous approaches suffer from a…