6 citations · 10 across the 19 of their papers we have counts for
19 papers
CRISP: Cliff-awaRe Input-adaptive Sparse Prefilling with Structural-Mass-Motivated Routing
Huu Huy Nguyen, Chien Van Nguyen, Franck Dernoncourt +4
The attention prefilling phase of long-context LLM inference scales quadratically, making self-attention a severe computational bottleneck. Traditional sparse attention methods mit…
Co-Evolving Graph and Text Memory for Training-Free Multi-Hop Question Answering
Hieu Man, Thien Huu Nguyen
Multi-hop question answering requires coordinating relational and textual evidence across reasoning steps, a combination neither a text corpus nor a knowledge graph can supply alon…
TALAS: Teacher-Anchored Layer Alignment with Adaptive Sharpness-Aware Minimization for Embedding Distillation
Quoc Phong Dao, Hoang Son Nguyen, Pham Khanh Chi +4
Knowledge Distillation (KD) has established itself as a pivotal technique for compressing large pre-trained language models. However, existing methods that force a student to stric…
Geometric and Stochastic Analysis of Discontinuities in Sparse Mixture-of-Experts
Tho Tran Huu, Huu-Tuan Nguyen, Thien-Hai Nguyen +4
Sparse Mixture-of-Experts (SMoE) architectures are now widely deployed in state-of-the-art language and vision models, where conditional routing allows scaling to very large networ…
Orthrus: Memory-Efficient Parallel Token Generation via Dual-View Diffusion
Chien Van Nguyen, Chaitra Hegde, Van Cuong Pham +3
We introduce Orthrus, a simple and efficient dual-architecture framework that unifies the exact generation fidelity of autoregressive Large Language Models (LLMs) with the high-spe…
Selective Off-Policy Reference Tuning with Plan Guidance
Duc Anh Le, Anh Duc, Tien-Phat Nguyen +3
Reinforcement learning with verifiable rewards helps reasoning, but GRPO-style methods stall on hard prompts where all sampled rollouts fail. SORT adds a repair update for those fa…
Explainable Disentangled Representation Learning for Generalizable Authorship Attribution in the Era of Generative AI
Hieu Man, Van-Cuong Pham, Nghia Trung Ngo +2
Learning robust representations of authorial style is crucial for authorship attribution and AI-generated text detection. However, existing methods often struggle with content-styl…
mSCoRe: a ultilingual and Scalable Benchmark for kill-based mmonsense asoning
Nghia Trung Ngo, Franck Dernoncourt, Thien Huu Nguyen
Recent advancements in reasoning-reinforced Large Language Models (LLMs) have shown remarkable capabilities in complex reasoning tasks. However, the mechanism underlying their util…
A Survey on Long-Video Storytelling Generation: Architectures, Consistency, and Cinematic Quality
Mohamed Elmoghany, Ryan Rossi, Seunghyun Yoon +26
Despite the significant progress that has been made in video generative models, existing state-of-the-art methods can only produce videos lasting 5-16 seconds, often labeled "long-…
Lizard: An Efficient Linearization Framework for Large Language Models
Chien Van Nguyen, Huy Nguyen, Ruiyi Zhang +10
We propose Lizard, a linearization framework that transforms pretrained Transformer-based Large Language Models (LLMs) into subquadratic architectures. Transformers faces severe co…
From Selection to Generation: A Survey of LLM-based Active Learning
Yu Xia, Subhojyoti Mukherjee, Zhouhang Xie +31
Active Learning (AL) has been a powerful paradigm for improving model efficiency and performance by selecting the most informative data points for labeling and training. In recent…
LUSIFER: Language Universal Space Integration for Enhanced Multilingual Embeddings with Large Language Models
Hieu Man, Nghia Trung Ngo, Viet Dac Lai +3
Recent advancements in large language models (LLMs) based embedding models have established new state-of-the-art benchmarks for text embedding tasks, particularly in dense vector-b…
GUI Agents: A Survey
Dang Nguyen, Jian Chen, Yu Wang +27
Graphical User Interface (GUI) agents, powered by Large Foundation Models, have emerged as a transformative approach to automating human-computer interaction. These agents autonomo…
Comprehensive and Practical Evaluation of Retrieval-Augmented Generation Systems for Medical Question Answering
Nghia Trung Ngo, Chien Van Nguyen, Franck Dernoncourt +1
Retrieval-augmented generation (RAG) has emerged as a promising approach to enhance the performance of large language models (LLMs) in knowledge-intensive tasks such as those from…
Zero-shot Cross-lingual Transfer Learning with Multiple Source and Target Languages for Information Extraction: Language Selection and Adversarial Training
Nghia Trung Ngo, Thien Huu Nguyen
The majority of previous researches addressing multi-lingual IE are limited to zero-shot cross-lingual single-transfer (one-to-one) setting, with high-resource languages predominan…
A Survey of Small Language Models
Chien Van Nguyen, Xuan Shen, Ryan Aponte +25
Small Language Models (SLMs) have become increasingly important due to their efficiency and performance to perform various language tasks with minimal computational resources, maki…
Taipan: Efficient and Expressive State Space Language Models with Selective Attention
Chien Van Nguyen, Huy Huu Nguyen, Thang M. Pham +8
Efficient long-context language modeling remains a significant challenge in Natural Language Processing (NLP). While Transformers dominate language tasks, they struggle with long s…
ULLME: A Unified Framework for Large Language Model Embeddings with Generation-Augmented Learning
Hieu Man, Nghia Trung Ngo, Franck Dernoncourt +1
Large Language Models (LLMs) excel in various natural language processing tasks, but leveraging them for dense passage embedding remains challenging. This is due to their causal at…
Identifying Speakers in Dialogue Transcripts: A Text-based Approach Using Pretrained Language Models
Minh Nguyen, Franck Dernoncourt, Seunghyun Yoon +6
We introduce an approach to identifying speaker names in dialogue transcripts, a crucial task for enhancing content accessibility and searchability in digital media archives. Despi…