53 citations · 282 across the 117 of their papers we have counts for
16 papers · 1 filter
DBCopilot: Natural Language Querying over Massive Databases via Schema Routing
Tianshu Wang, Xiaoyang Chen, Hongyu Lin +4
The development of Natural Language Interfaces to Databases (NLIDBs) has been greatly advanced by the advent of large language models (LLMs), which provide an intuitive way to tran…
Mitigating Large Language Model Hallucinations via Autonomous Knowledge Graph-based Retrofitting
Xinyan Guan, Yanjiang Liu, Hongyu Lin +4
Incorporating factual knowledge in knowledge graph is regarded as a promising approach for mitigating the hallucination of large language models (LLMs). Existing methods usually on…
Toward Unified Controllable Text Generation via Regular Expression Instruction
Xin Zheng, Hongyu Lin, Xianpei Han +1
Controllable text generation is a fundamental aspect of natural language generation, with numerous methods proposed for different constraint types. However, these approaches often…
Benchmarking Large Language Models in Retrieval-Augmented Generation
Jiawei Chen, Hongyu Lin, Xianpei Han +1
Retrieval-Augmented Generation (RAG) is a promising approach for mitigating the hallucination of large language models (LLMs). However, existing research lacks rigorous evaluation…
Defense of Adversarial Ranking Attack in Text Retrieval: Benchmark and Baseline via Detection
Xuanang Chen, Ben He, Le Sun +1
Neural ranking models (NRMs) have undergone significant development and have become integral components of information retrieval (IR) systems. Unfortunately, recent research has un…
ToolAlpaca: Generalized Tool Learning for Language Models with 3000 Simulated Cases
Qiaoyu Tang, Ziliang Deng, Hongyu Lin +4
Enabling large language models to utilize real-world tools effectively is crucial for achieving embodied intelligence. Existing approaches to tool learning have either primarily re…