activity
20152026
most citedAffective EEG-Based Person Identification Using the Deep Learning Approach

174 citations · 462 across the 32 of their papers we have counts for

collaborators

34 papers

cs.CL2026

SEA-CLIP-Tiny: Efficient Multilingual Text-Vision Embedding for Southeast Asian Languages

Puja Ahmad Habibi, Faiz Assabil Firdaus, Ashvanth S +3

Multilingual text-vision embedding models are essential for cross-lingual image-text retrieval, but Southeast Asian languages remain poorly supported due to the region's linguistic…

cs.CL2026

Exploring Extrinsic and Intrinsic Properties for Effective Reasoning with Code Interpreter

Patomporn Payoungkhamdee, Napat Laosaengpha, Jenta Wonglertsakul +8

Reasoning with a Code Interpreter (CI) has emerged as an effective paradigm for enhancing the reasoning capabilities of large language models (LLMs) through executable computation…

cs.IR2025

Evaluating Perspectival Biases in Cross-Modal Retrieval

Teerapol Saengsukhiran, Peerawat Chomphooyod, Narabodee Rodjananant +6

Multimodal retrieval systems are expected to operate in a semantic space, agnostic to the language or cultural origin of the query. In practice, however, retrieval outcomes systema…

cs.CL2025

SEADialogues: A Multilingual Culturally Grounded Multi-turn Dialogue Dataset on Southeast Asian Languages

Muhammad Dehan Al Kautsar, Aswin Candra, Muhammad Alif Al Hakim +6

Although numerous datasets have been developed to support dialogue systems, most existing chit-chat datasets overlook the cultural nuances inherent in natural human conversations.…

cs.CL2025

SEA-BED: How Do Embedding Models Represent Southeast Asian Languages?

Wuttikorn Ponwitayarat, Peerat Limkonchotiwat, Raymond Ng +9

Multilingual text embeddings are often assumed to encode meaning in a perspective-independent semantic space, yielding stable similarity judgments across tasks and languages. Our r…

cs.RO2025

Spatial Language Likelihood Grounding Network for Bayesian Fusion of Human-Robot Observations

Supawich Sitdhipol, Waritwong Sukprasongdee, Ekapol Chuangsuwanich +1

Fusing information from human observations can help robots overcome sensing limitations in collaborative tasks. However, an uncertainty-aware fusion framework requires a grounded l…