most citedMapping the Media Landscape: Predicting Factual Reporting and Political Bias Through Web Interactions

2 citations · 2 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL2026

DialFork: Going Beyond Factuality to Evaluate Procedural Hallucination in Conversational Agents

Sergio Burdisso, Esaú Villatoro-Tello, Dairazalia Sánchez-Cortés +4

Large language models (LLMs) deployed as conversational agents are increasingly expected to follow procedural logic. While factual hallucination has received extensive attention, a…

cs.CL2026

How to Leverage Synthetic Speech for LLM-Based ASR Systems?

Yanis Labrak, Dairazalia Sanchez-Cortes, Sergio Burdisso +9

In regulated domains such as banking and healthcare, where privacy constraints make real speech costly to collect and retain, synthetic speech from modern text-to-speech (TTS) is a…

cs.CL2026

Closing the Speech-Text Gap with Limited Audio for Effective Domain Adaptation in LLM-Based ASR

Thibault Bañeras-Roux, Sergio Burdisso, Esaú Villatoro-Tello +9

Conventional end-to-end automatic speech recognition (ASR) systems rely on paired speech-text data for domain adaptation. Recent LLM-based ASR architectures connect a speech encode…

cs.CL2026

Abstract Compression of Conversational Audio Context for LLM-based ASR

Shashi Kumar, Esaú Villatoro-Tello, Sergio Burdisso +7

Standard LLM-based speech recognition systems process utterances in isolation, limiting their ability to leverage conversational context. Here we study whether multimodal context f…

cs.AI2024★ 2 cited

Mapping the Media Landscape: Predicting Factual Reporting and Political Bias Through Web Interactions

Dairazalia Sánchez-Cortés, Sergio Burdisso, Esaú Villatoro-Tello +1

Bias assessment of news sources is paramount for professionals, organizations, and researchers who rely on truthful evidence for information gathering and reporting. While certain…