6 citations · 6 across the 10 of their papers we have counts for
11 papers
Chain Of Thought Compression: A Theoretical Analysis
Juncai Li, Ru Li, Yuxiang Zhou +2
Chain-of-Thought (CoT) has unlocked advanced reasoning abilities of Large Language Models (LLMs) with intermediate steps, yet incurs prohibitive computational costs due to generati…
Consistency-Aware Editing for Entity-level Unlearning in Language Models
Xiaoqi Han, Víctor Gutiérrez-Basulto, Ru Li +3
Large language models (LLMs) risk retaining sensitive, copyrighted, or harmful information from their training data. Entity-level unlearning addresses this issue by removing all kn…
Uncovering and Mitigating Transient Blindness in Multimodal Model Editing
Xiaoqi Han, Ru Li, Ran Yi +4
Multimodal Model Editing (MMED) aims to correct erroneous knowledge in multimodal models. Existing evaluation methods, adapted from textual model editing, overstate success by rely…
Multi-level Mixture of Experts for Multimodal Entity Linking
Zhiwei Hu, Víctor Gutiérrez-Basulto, Zhiliang Xiang +2
Multimodal Entity Linking (MEL) aims to link ambiguous mentions within multimodal contexts to associated entities in a multimodal knowledge base. Existing approaches to MEL introdu…
COTET: Cross-view Optimal Transport for Knowledge Graph Entity Typing
Zhiwei Hu, Víctor Gutiérrez-Basulto, Zhiliang Xiang +2
Knowledge graph entity typing (KGET) aims to infer missing entity type instances in knowledge graphs. Previous research has predominantly centered around leveraging contextual info…
Leveraging Intra-modal and Inter-modal Interaction for Multi-Modal Entity Alignment
Zhiwei Hu, Víctor Gutiérrez-Basulto, Zhiliang Xiang +2
Multi-modal entity alignment (MMEA) aims to identify equivalent entity pairs across different multi-modal knowledge graphs (MMKGs). Existing approaches focus on how to better encod…
HyperMono: A Monotonicity-aware Approach to Hyper-Relational Knowledge Representation
Zhiwei Hu, Víctor Gutiérrez-Basulto, Zhiliang Xiang +2
In a hyper-relational knowledge graph (HKG), each fact is composed of a main triple associated with attribute-value qualifiers, which express additional factual knowledge. The hype…
Knowledge-Aware Neuron Interpretation for Scene Classification
Yong Guan, Freddy Lecue, Jiaoyan Chen +2
Although neural models have achieved remarkable performance, they still encounter doubts due to the intransparency. To this end, model prediction explanation is attracting more and…
Multi-view Contrastive Learning for Entity Typing over Knowledge Graphs
Zhiwei Hu, Víctor Gutiérrez-Basulto, Zhiliang Xiang +2
Knowledge graph entity typing (KGET) aims at inferring plausible types of entities in knowledge graphs. Existing approaches to KGET focus on how to better encode the knowledge prov…
Transformer-based Entity Typing in Knowledge Graphs
Zhiwei Hu, Víctor Gutiérrez-Basulto, Zhiliang Xiang +2
We investigate the knowledge graph entity typing task which aims at inferring plausible entity types. In this paper, we propose a novel Transformer-based Entity Typing (TET) approa…
Type-aware Embeddings for Multi-Hop Reasoning over Knowledge Graphs
Zhiwei Hu, Víctor Gutiérrez-Basulto, Zhiliang Xiang +3
Multi-hop reasoning over real-life knowledge graphs (KGs) is a highly challenging problem as traditional subgraph matching methods are not capable to deal with noise and missing in…