most citedUniversal Information Extraction as Unified Semantic Matching

7 citations · 11 across the 7 of their papers we have counts for

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cs.CL2024

URL: Universal Referential Knowledge Linking via Task-instructed Representation Compression

Zhuoqun Li, Hongyu Lin, Tianshu Wang +7

Linking a claim to grounded references is a critical ability to fulfill human demands for authentic and reliable information. Current studies are limited to specific tasks like inf…

cs.CL2024

Few-shot Named Entity Recognition via Superposition Concept Discrimination

Jiawei Chen, Hongyu Lin, Xianpei Han +4

Few-shot NER aims to identify entities of target types with only limited number of illustrative instances. Unfortunately, few-shot NER is severely challenged by the intrinsic preci…

cs.CL20241 cited

Meta-Cognitive Analysis: Evaluating Declarative and Procedural Knowledge in Datasets and Large Language Models

Zhuoqun Li, Hongyu Lin, Yaojie Lu +3

Declarative knowledge and procedural knowledge are two key parts in meta-cognitive theory, and these two hold significant importance in pre-training and inference of LLMs. However,…

cs.CL2024

Executing Natural Language-Described Algorithms with Large Language Models: An Investigation

Xin Zheng, Qiming Zhu, Hongyu Lin +3

Executing computer programs described in natural language has long been a pursuit of computer science. With the advent of enhanced natural language understanding capabilities exhib…

cs.CL20233 cited

Learning In-context Learning for Named Entity Recognition

Jiawei Chen, Yaojie Lu, Hongyu Lin +7

Named entity recognition in real-world applications suffers from the diversity of entity types, the emergence of new entity types, and the lack of high-quality annotations. To addr…

cs.CL2023

Harvesting Event Schemas from Large Language Models

Jialong Tang, Hongyu Lin, Zhuoqun Li +3

Event schema provides a conceptual, structural and formal language to represent events and model the world event knowledge. Unfortunately, it is challenging to automatically induce…