Papers by Anh Luu
Improving Multimodal Sentiment Analysis: Supervised Angular margin-based Contrastive Learning for Enhanced Fusion Representation (2023.findings-emnlp)
Copied to clipboard
| Challenge: | Existing methods for multimodal sentiment analysis focus on forming positive and negative pairs, neglecting the variation in sentiment scores within the same class. |
| Approach: | They propose a framework to enhance discrimination and generalizability of the multimodal representation and overcome biases in the fusion vector’s modality. |
| Outcome: | The proposed model improves discrimination and generalizability of the multimodal representation and overcomes biases in the fusion vector’s modality. |
A Parallel Corpus for Vietnamese Central-Northern Dialect Text Transfer (2023.findings-emnlp)
Copied to clipboard
| Challenge: | Among these, the northern dialect is often treated as the standard i.e. the defacto text style of the language. |
| Approach: | They propose a parallel corpus for Vietnamese central-northern dialect text transfer to facilitate research on this domain. |
| Outcome: | The proposed model improves existing models on the central dialect domain with dedicated results in translation and text-image retrieval tasks. |
Three Minds, One Legend: Jailbreak Large Reasoning Model with Adaptive Stacked Ciphers (2026.findings-acl)
Copied to clipboard
| Challenge: | Existing jailbreak methods struggle to balance effectiveness with robustness against adaptive safety mechanisms. |
| Approach: | They propose a novel approach that targets Large Reasoning Models through an adaptive encryption pipeline designed to overwhelm their reasoning capabilities. |
| Outcome: | The proposed approach achieves an attack success rate of 85.6% on OpenAI GPT-o4-mini, outperforming state-of-the-art baselines by a significant margin of 17.2%. |
DemaFormer: Damped Exponential Moving Average Transformer with Energy-Based Modeling for Temporal Language Grounding (2023.findings-emnlp)
Copied to clipboard
| Challenge: | Temporal Language Grounding (TLG) is a task to determine temporal boundaries of video moments that correspond to a language query. |
| Approach: | They propose an energy-based model framework to explicitly learn moment-query distributions. |
| Outcome: | The proposed model outperforms the state-of-the-art models on four public temporal language grounding datasets. |
Enhancing Multimodal Entity Linking with Jaccard Distance-based Conditional Contrastive Learning and Contextual Visual Augmentation (2025.naacl-long)
Copied to clipboard
Cong-Duy T Nguyen, Xiaobao Wu, Thong Thanh Nguyen, Shuai Zhao, Khoi M. Le, Nguyen Viet Anh, Feng Yichao, Anh Tuan Luu
| Challenge: | Existing approaches to multimodal entity linking use contrastive learning to align input sentences and entities, but are limited by their random negative sampling. |
| Approach: | They propose a method to match negative samples with similar attributes using JD-CCL . they also propose 'contextual visual-aid controllable patch transform' experimental results demonstrate the strong effectiveness of their method . |
| Outcome: | The proposed method is able to match negative samples with similar attributes on a multimodal knowledge graph. |
Exploiting Contrastive Learning and Numerical Evidence for Confusing Legal Judgment Prediction (2023.findings-emnlp)
Copied to clipboard
| Challenge: | Existing studies fail to distinguish different classification errors with a standard cross-entropy classification loss and ignore the numbers in the fact description for predicting the term of penalty. |
| Approach: | They propose to extract crime amounts from fact description and use them to learn distinguishable representations to exploit the numbers in the fact description for predicting the term of penalty. |
| Outcome: | The proposed method achieves state-of-the-art results on real-world datasets and ablation studies demonstrate the effectiveness of each component. |
Prompt as Triggers for Backdoor Attack: Examining the Vulnerability in Language Models (2023.emnlp-main)
Copied to clipboard
| Challenge: | ProAttack is a novel and efficient method for performing clean-label backdoor attacks based on the prompt, which uses the prompt itself as a trigger. |
| Approach: | They propose a method for performing clean-label backdoor attacks based on the prompt, which uses the prompt itself as a trigger. |
| Outcome: | The proposed method achieves state-of-the-art performance on several NLP tasks, particularly in few-shot settings. |
Rethinking Negative Pairs in Code Search (2023.emnlp-main)
Copied to clipboard
| Challenge: | Comparative learning is a key component in fine-tuning code search models . however, negative samples of InfoNCE may deteriorate its representation learning . |
| Approach: | They propose a loss function that inserts weight terms into InfoNCE to improve contrastive learning. |
| Outcome: | The proposed loss function is a special case of Soft-InfoNCE, the authors show . it is more accurate than other loss functions, and it is faster than other models. |
A Spectral Viewpoint on Continual Relation Extraction (2023.findings-emnlp)
Copied to clipboard
| Challenge: | Existing methods to solve the Continual Relation Extraction problem have been proposed . |
| Approach: | They propose a class-wise regularization method that preserves eigenvectors for each class shape . they propose spectral regularization to preserve eenvector shape after learning new tasks . |
| Outcome: | The proposed method improves performance on two benchmark datasets. |