18 citations · 81 across the 15 of their papers we have counts for
9 papers · 1 filter
Internal Value Alignment in Large Language Models through Controlled Value Vector Activation
Haoran Jin, Meng Li, Xiting Wang +4
Aligning Large Language Models (LLMs) with human values has attracted increasing attention since it provides clarity, transparency, and the ability to adapt to evolving scenarios.…
ICLEval: Evaluating In-Context Learning Ability of Large Language Models
Wentong Chen, Yankai Lin, ZhenHao Zhou +4
In-Context Learning (ICL) is a critical capability of Large Language Models (LLMs) as it empowers them to comprehend and reason across interconnected inputs. Evaluating the ICL abi…
Learning Entity Linking Features for Emerging Entities
Chenwei Ran, Wei Shen, Jianbo Gao +3
Entity linking (EL) is the process of linking entity mentions appearing in text with their corresponding entities in a knowledge base. EL features of entities (e.g., prior probabil…
KMIR: A Benchmark for Evaluating Knowledge Memorization, Identification and Reasoning Abilities of Language Models
Daniel Gao, Yantao Jia, Lei Li +6
Previous works show the great potential of pre-trained language models (PLMs) for storing a large amount of factual knowledge. However, to figure out whether PLMs can be reliable k…
Towards More Effective and Economic Sparsely-Activated Model
Hao Jiang, Ke Zhan, Jianwei Qu +14
The sparsely-activated models have achieved great success in natural language processing through large-scale parameters and relatively low computational cost, and gradually become…
Emotion Eliciting Machine: Emotion Eliciting Conversation Generation based on Dual Generator
Hao Jiang, Yutao Zhu, Xinyu Zhang +4
Recent years have witnessed great progress on building emotional chatbots. Tremendous methods have been proposed for chatbots to generate responses with given emotions. However, th…
FedE: Embedding Knowledge Graphs in Federated Setting
Mingyang Chen, Wen Zhang, Zonggang Yuan +2
Knowledge graphs (KGs) consisting of triples are always incomplete, so it's important to do Knowledge Graph Completion (KGC) by predicting missing triples. Multi-Source KG is a com…
Jointly Modeling Hierarchical and Horizontal Features for Relational Triple Extraction
Zhepei Wei, Yantao Jia, Yuan Tian +4
Recent works on relational triple extraction have shown the superiority of jointly extracting entities and relations over the pipelined extraction manner. However, most existing jo…
Path-Based Attention Neural Model for Fine-Grained Entity Typing
Denghui Zhang, Pengshan Cai, Yantao Jia +3
Fine-grained entity typing aims to assign entity mentions in the free text with types arranged in a hierarchical structure. Traditional distant supervision based methods employ a s…