activity
20202026
most citedMEDITRON-70B: Scaling Medical Pretraining for Large Language Models

123 citations · 179 across the 15 of their papers we have counts for

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10 papers · 1 filter

cs.CL2025

Measuring what Matters: Construct Validity in Large Language Model Benchmarks

Andrew M. Bean, Ryan Othniel Kearns, Angelika Romanou +39

Evaluating large language models (LLMs) is crucial for both assessing their capabilities and identifying safety or robustness issues prior to deployment. Reliably measuring abstrac…

cs.CL2025

Apertus: Democratizing Open and Compliant LLMs for Global Language Environments

Project Apertus, Alejandro Hernández-Cano, Alexander Hägele +100

We present Apertus, a fully open suite of large language models (LLMs) designed to address two systemic shortcomings in today's open model ecosystem: data compliance and multilingu…

cs.CL2025

PERK: Long-Context Reasoning as Test-Time Learning

Zeming Chen, Angelika Romanou, Gail Weiss +1

Long-context reasoning requires accurately identifying relevant information in extensive, noisy input contexts. In this work, we propose PERK (Parameter Efficient Reasoning over Kn…

cs.CL2025

WikiMixQA: A Multimodal Benchmark for Question Answering over Tables and Charts

Negar Foroutan, Angelika Romanou, Matin Ansaripour +3

Documents are fundamental to preserving and disseminating information, often incorporating complex layouts, tables, and charts that pose significant challenges for automatic docume…

cs.CL2025

Balancing Knowledge Delivery and Emotional Comfort in Healthcare Conversational Systems

Shang-Chi Tsai, Yun-Nung Chen

With the advancement of large language models, many dialogue systems are now capable of providing reasonable and informative responses to patients' medical conditions. However, whe…

cs.CL2025

Kaleidoscope: In-language Exams for Massively Multilingual Vision Evaluation

Israfel Salazar, Manuel Fernández Burda, Shayekh Bin Islam +42

The evaluation of vision-language models (VLMs) has mainly relied on English-language benchmarks, leaving significant gaps in both multilingual and multicultural coverage. While mu…

cs.CL2024★ 6 cited

Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluation

Shivalika Singh, Angelika Romanou, Clémentine Fourrier +21

Cultural biases in multilingual datasets pose significant challenges for their effectiveness as global benchmarks. These biases stem not only from differences in language but also…

cs.CL2024★ 4 cited

INCLUDE: Evaluating Multilingual Language Understanding with Regional Knowledge

Angelika Romanou, Negar Foroutan, Anna Sotnikova +56

The performance differential of large language models (LLM) between languages hinders their effective deployment in many regions, inhibiting the potential economic and societal val…

cs.CL2023★ 123 cited

MEDITRON-70B: Scaling Medical Pretraining for Large Language Models

Zeming Chen, Alejandro Hernández Cano, Angelika Romanou +17

Large language models (LLMs) can potentially democratize access to medical knowledge. While many efforts have been made to harness and improve LLMs' medical knowledge and reasoning…

cs.CL2023

CRAB: Assessing the Strength of Causal Relationships Between Real-world Events

Angelika Romanou, Syrielle Montariol, Debjit Paul +3

Understanding narratives requires reasoning about the cause-and-effect relationships between events mentioned in the text. While existing foundation models yield impressive results…