activity
20232026
most citedDomain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

74 citations · 87 across the 14 of their papers we have counts for

collaborators
Showing 2023Show all

6 papers · 1 filter

cs.CL2023★ 1 cited

Open-ended Commonsense Reasoning with Unrestricted Answer Scope

Chen Ling, Xuchao Zhang, Xujiang Zhao +7

Open-ended Commonsense Reasoning is defined as solving a commonsense question without providing 1) a short list of answer candidates and 2) a pre-defined answer scope. Conventional…

cs.CL2023★ 2 cited

Improving Open Information Extraction with Large Language Models: A Study on Demonstration Uncertainty

Chen Ling, Xujiang Zhao, Xuchao Zhang +8

Open Information Extraction (OIE) task aims at extracting structured facts from unstructured text, typically in the form of (subject, relation, object) triples. Despite the potenti…

cs.LG2023

Towards Counterfactual Fairness-aware Domain Generalization in Changing Environments

Yujie Lin, Chen Zhao, Minglai Shao +3

Recognizing the prevalence of domain shift as a common challenge in machine learning, various domain generalization (DG) techniques have been developed to enhance the performance o…

cs.AI2023

Adaptation Speed Analysis for Fairness-aware Causal Models

Yujie Lin, Chen Zhao, Minglai Shao +2

For example, in machine translation tasks, to achieve bidirectional translation between two languages, the source corpus is often used as the target corpus, which involves the trai…

cs.CL2023★ 74 cited

Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

Chen Ling, Xujiang Zhao, Jiaying Lu +21

Large language models (LLMs) have significantly advanced the field of natural language processing (NLP), providing a highly useful, task-agnostic foundation for a wide range of app…

cs.AI2023★ 7 cited

Knowledge-enhanced Neural Machine Reasoning: A Review

Tanmoy Chowdhury, Chen Ling, Xuchao Zhang +5

Knowledge-enhanced neural machine reasoning has garnered significant attention as a cutting-edge yet challenging research area with numerous practical applications. Over the past f…