HEALTHDIAL is a multilingual multi-parallel spoken dialogue dataset containing 1,500 dialogues per language grounded in WHO content, with recorded speech and speaker metadata across four languages.
arXiv preprint arXiv:2503.10497 , year=
7 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
representative citing papers
Audited olympiad corpus and Physics-R1 recipe improve 8B VLM by up to 18 points on held-out physics problems while exposing contamination in prior evals.
Domain-adaptive pre-training on a new French health corpus yields limited gains and risks general capability loss unless followed by model merging, which can even boost specialized performance.
COMPASS uses semantic clustering on multilingual embeddings to select auxiliary data for PEFT adapters, outperforming linguistic-similarity baselines on multilingual benchmarks while supporting continual adaptation.
LANG combines language-adaptive hint guidance, progressive decay, and difficulty-tailored learning horizons in RL to boost non-English reasoning performance while preserving language consistency.
Multilingual reasoning gaps in RLMs arise primarily from language understanding failures that can be detected and mitigated by selectively translating inputs to English.
Modifying nationality and language parameters in English-centric personas for mental health dialogues introduces clinical inconsistencies across languages and causes LLM judges to perform inaccurately on non-English depression severity assessments.
citing papers explorer
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Dial HEALTHDIAL for Advice: A Multilingual and Multi-Parallel Spoken Dialogue Dataset for Knowledge-Grounded Information Seeking
HEALTHDIAL is a multilingual multi-parallel spoken dialogue dataset containing 1,500 dialogues per language grounded in WHO content, with recorded speech and speaker metadata across four languages.
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Physics-R1: An Audited Olympiad Corpus and Recipe for Visual Physics Reasoning
Audited olympiad corpus and Physics-R1 recipe improve 8B VLM by up to 18 points on held-out physics problems while exposing contamination in prior evals.
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Is Biomedical Specialization Still Worth It? Insights from Domain-Adaptive Language Modelling with a New French Health Corpus
Domain-adaptive pre-training on a new French health corpus yields limited gains and risks general capability loss unless followed by model merging, which can even boost specialized performance.
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COMPASS: COntinual Multilingual PEFT with Adaptive Semantic Sampling
COMPASS uses semantic clustering on multilingual embeddings to select auxiliary data for PEFT adapters, outperforming linguistic-similarity baselines on multilingual benchmarks while supporting continual adaptation.
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LANG: Reinforcement Learning for Multilingual Reasoning with Language-Adaptive Hint Guidance
LANG combines language-adaptive hint guidance, progressive decay, and difficulty-tailored learning horizons in RL to boost non-English reasoning performance while preserving language consistency.
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Why Do Multilingual Reasoning Gaps Emerge in Reasoning Language Models?
Multilingual reasoning gaps in RLMs arise primarily from language understanding failures that can be detected and mitigated by selectively translating inputs to English.
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Creating Multilingual Mental Health Dialogue Datasets: Limits of Persona-Based Localization via Nationality and Language
Modifying nationality and language parameters in English-centric personas for mental health dialogues introduces clinical inconsistencies across languages and causes LLM judges to perform inaccurately on non-English depression severity assessments.