activity
20242026
collaborators

7 papers

cs.CL2026

thaulab@EEUCA 2026: Who Said What to Whom? A Targeting-Aware Neural-Symbolic Pipeline for Gaming Toxicity Detection

Anmol Guragain, Marcos Estecha-Garitagoitia, Luis Fernando D'Haro Enríquez +1

This paper describes our system for the EEUCA 2026 Shared Task on toxicity classification in gaming chat. We implement a three-stage pipeline combining an ensemble of two compact t…

cs.CL2025

Overview of Dialog System Evaluation Track: Dimensionality, Language, Culture and Safety at DSTC 12

John Mendonça, Lining Zhang, Rahul Mallidi +4

The rapid advancement of Large Language Models (LLMs) has intensified the need for robust dialogue system evaluation, yet comprehensive assessment remains challenging. Traditional…

cs.CL2025

Commonsense Generation and Evaluation for Dialogue Systems using Large Language Models

Marcos Estecha-Garitagoitia, Chen Zhang, Mario Rodríguez-Cantelar +1

This paper provides preliminary results on exploring the task of performing turn-level data augmentation for dialogue system based on different types of commonsense relationships,…

cs.CL2025

Unsupervised Mutual Learning of Discourse Parsing and Topic Segmentation in Dialogue

Jiahui Xu, Feng Jiang, Anningzhe Gao +2

In dialogue systems, discourse plays a crucial role in managing conversational focus and coordinating interactions. It consists of two key structures: rhetorical structure and topi…

cs.SD2024

Beyond Single-Audio: Advancing Multi-Audio Processing in Audio Large Language Models

Yiming Chen, Xianghu Yue, Xiaoxue Gao +4

Various audio-LLMs (ALLMs) have been explored recently for tackling different audio tasks simultaneously using a single, unified model. While existing evaluations of ALLMs primaril…

cs.CV2024

CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark

David Romero, Chenyang Lyu, Haryo Akbarianto Wibowo +73

Visual Question Answering (VQA) is an important task in multimodal AI, and it is often used to test the ability of vision-language models to understand and reason on knowledge pres…