31 citations · 160 across the 55 of their papers we have counts for
60 papers
Event Interaction in Low-Rank Bottlenecks for Temporal Relation Extraction
Wei Sun, Tingyu Qu, Jesse Davis +1
Temporal relation extraction determines whether an event occurs before, after, or simultaneously with another event, and therefore relies on accurately modeling how the two events…
Cross-lingual Representation Learning via Centroid Intervention Fusion
Wei Sun, Marie-Francine Moens
Large language models (LLMs) exhibit uneven multilingual performance, especially when dealing with low-resource languages. Inference-time intervention offers a lightweight way to i…
What Makes Linguistic Representations Good Models of High-Level Visual Perception in the Human Brain?
Anna Bavaresco, Ina Klarić, Raquel Fernández +1
Image descriptions represented with language models (LMs) predict human brain responses to naturalistic images in high-level visual regions, but the factors driving this predictivi…
ClimateCause: Complex and Implicit Causal Structures in Climate Reports
Liesbeth Allein, Nataly Pineda-Castañeda, Andrea Rocci +1
Understanding climate change requires reasoning over complex causal networks. Yet, existing causal discovery datasets predominantly capture explicit, direct causal relations. We in…
Assessing LLM Reasoning Through Implicit Causal Chain Discovery in Climate Discourse
Liesbeth Allein, Nataly Pineda-Castañeda, Andrea Rocci +1
How does a cause lead to an effect, and which intermediate causal steps explain their connection? This work scrutinizes the mechanistic causal reasoning capabilities of large langu…
Automated Prompt Generation for Creative and Counterfactual Text-to-image Synthesis
Aleksa Jelaca, Ying Jiao, Chang Tian +1
Text-to-image generation has advanced rapidly with large-scale multimodal training, yet fine-grained controllability remains a critical challenge. Counterfactual controllability, d…
Structured Information for Improving Spatial Relationships in Text-to-Image Generation
Sander Schildermans, Chang Tian, Ying Jiao +1
Text-to-image (T2I) generation has advanced rapidly, yet faithfully capturing spatial relationships described in natural language prompts remains a major challenge. Prior efforts h…
Bridging Language Gaps: Enhancing Few-Shot Language Adaptation
Philipp Borchert, Jochen De Weerdt, Marie-Francine Moens
The disparity in language resources poses a challenge in multilingual NLP, with high-resource languages benefiting from extensive data, while low-resource languages lack sufficient…
Large Language Models Reasoning Abilities Under Non-Ideal Conditions After RL-Fine-Tuning
Chang Tian, Matthew B. Blaschko, Mingzhe Xing +3
Reinforcement learning (RL) has become a key technique for enhancing the reasoning abilities of large language models (LLMs), with policy-gradient algorithms dominating the post-tr…
Mitigating Negative Interference in Multilingual Sequential Knowledge Editing through Null-Space Constraints
Wei Sun, Tingyu Qu, Mingxiao Li +2
Efficiently updating multilingual knowledge in large language models (LLMs), while preserving consistent factual representations across languages, remains a long-standing and unres…
Consistent Story Generation: Unlocking the Potential of Zigzag Sampling
Mingxiao Li, Mang Ning, Marie-Francine Moens
Text-to-image generation models have made significant progress in producing high-quality images from textual descriptions, yet they continue to struggle with maintaining subject co…
Using Causality for Enhanced Prediction of Web Traffic Time Series
Chang Tian, Mingzhe Xing, Zenglin Shi +3
Predicting web service traffic has significant social value, as it can be applied to various practical scenarios, including but not limited to dynamic resource scaling, load balanc…
Language Fusion for Parameter-Efficient Cross-lingual Transfer
Philipp Borchert, Ivan Vulić, Marie-Francine Moens +1
Limited availability of multilingual text corpora for training language models often leads to poor performance on downstream tasks due to undertrained representation spaces for lan…
Action-based image editing guided by human instructions
Maria Mihaela Trusca, Mingxiao Li, Marie-Francine Moens
Text-based image editing is typically approached as a static task that involves operations such as inserting, deleting, or modifying elements of an input image based on human instr…
Fighting Against the Repetitive Training and Sample Dependency Problem in Few-shot Named Entity Recognition
Chang Tian, Wenpeng Yin, Dan Li +1
Few-shot named entity recognition (NER) systems recognize entities using a few labeled training examples. The general pipeline consists of a span detector to identify entity spans…
A Generic Method for Fine-grained Category Discovery in Natural Language Texts
Chang Tian, Matthew B. Blaschko, Wenpeng Yin +3
Fine-grained category discovery using only coarse-grained supervision is a cost-effective yet challenging task. Previous training methods focus on aligning query samples with posit…
DistilDoc: Knowledge Distillation for Visually-Rich Document Applications
Jordy Van Landeghem, Subhajit Maity, Ayan Banerjee +4
This work explores knowledge distillation (KD) for visually-rich document (VRD) applications such as document layout analysis (DLA) and document image classification (DIC). While V…
Multimodal Adaptive Inference for Document Image Classification with Anytime Early Exiting
Omar Hamed, Souhail Bakkali, Marie-Francine Moens +2
This work addresses the need for a balanced approach between performance and efficiency in scalable production environments for visually-rich document understanding (VDU) tasks. Cu…
MSNER: A Multilingual Speech Dataset for Named Entity Recognition
Quentin Meeus, Marie-Francine Moens, Hugo Van hamme
While extensively explored in text-based tasks, Named Entity Recognition (NER) remains largely neglected in spoken language understanding. Existing resources are limited to a singl…
DMON: A Simple yet Effective Approach for Argument Structure Learning
Wei Sun, Mingxiao Li, Jingyuan Sun +2
Argument structure learning~(ASL) entails predicting relations between arguments. Because it can structure a document to facilitate its understanding, it has been widely applied in…
Efficient Information Extraction in Few-Shot Relation Classification through Contrastive Representation Learning
Philipp Borchert, Jochen De Weerdt, Marie-Francine Moens
Differentiating relationships between entity pairs with limited labeled instances poses a significant challenge in few-shot relation classification. Representations of textual data…
Computational Models to Study Language Processing in the Human Brain: A Survey
Shaonan Wang, Jingyuan Sun, Yunhao Zhang +3
Despite differing from the human language processing mechanism in implementation and algorithms, current language models demonstrate remarkable human-like or surpassing language ca…
NeuroCine: Decoding Vivid Video Sequences from Human Brain Activties
Jingyuan Sun, Mingxiao Li, Zijiao Chen +1
In the pursuit to understand the intricacies of human brain's visual processing, reconstructing dynamic visual experiences from brain activities emerges as a challenging yet fascin…
Explicitly Representing Syntax Improves Sentence-to-layout Prediction of Unexpected Situations
Wolf Nuyts, Ruben Cartuyvels, Marie-Francine Moens
Recognizing visual entities in a natural language sentence and arranging them in a 2D spatial layout require a compositional understanding of language and space. This task of layou…