13 papers
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…
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…
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…
Decom-Renorm-Merge: Model Merging on the Right Space Improves Multitasking
Yuatyong Chaichana, Thanapat Trachu, Peerat Limkonchotiwat +3
In the era of large-scale training, model merging has evolved into a tool for creating multitasking models efficiently. It enables the knowledge of models to be fused, without the…
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.…
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…