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Thien Huu Nguyen

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Review Sep 2026

Joint and Cross-Modal Video-Audio Generation and Editing: A Unified Formulation and Design Taxonomy

Video and audio are perceived together, yet most generative models treat them in isolation. We examine methods that model the two modalities jointly, generate one from the other, or edit them in a coupled manner, organized around a single question: how is the output kept coherent across modalities in time and semantics...

Abhinav Sharma, S. Navuluru, Wang Wei et al. · 0 citations
Jul 2026

Co-Evolving Graph and Text Memory for Training-Free Multi-Hop Question Answering

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 alone. Prior work often emphasizes only part of this loop: graph-augmented RAG retrieves from a pre-built or query-updated graph, KGQA systems s...

Hieu Man, T. Nguyen · 0 citations
#machine learning Preprint Sep 2026

CRISP: Cliff-awaRe Input-adaptive Sparse Prefilling with Structural-Mass-Motivated Routing

This work replaces the Jensen-Shannon Divergence routing with C_struct, a structural proxy that measures mass at Vertical-Slash compatible positions and reproduces JSD's routing decisions while eliminating both the pooled matmul and subsequent KL divergence overhead.

H. Nguyen, Chien Van Nguyen, Franck Dernoncourt et al. · 0 citations
Conference Open access 2026

Towards Fast and Accurate Modeling for Cross-Lingual Label Projection

This work proposes to synthesize alignment sequence pairs and fine-tune an encoder model with span alignment objective and introduces EXP - the first benchmark for explicit evaluation of label projection, thereby reducing confounders and non-determinism in method assessment.

Thang Le, Huy Huu Nguyen, A. Luu et al. · 0 citations
Conference Open access 2026

Octopus: Gated Selective Attention for Memory-Bounded Long-Context Inference in Large Language Models

O CTOPUS is proposed, a framework that confers fixed-memory inference onto pretrained Transform-ers without the information loss of linearization and outperforms state-of-the-art linearized baselines on the GSM8K benchmark, demonstrating that learned sparse retention serves as an effective regular-izer for long-horizon...

C. Nguyen, Ryan A. Rossi, L. Van et al. · 0 citations

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