1 citations · 1 across the 10 of their papers we have counts for
11 papers
CLIMB: A Clinical Multimorbidity Benchmark for Diagnosing Co-occurring Conditions through Multiturn Conversations
Yusuf Kesmen, Aniruddha Mukherjee, Yena Chang +7
Patients often have several co-occurring clinical conditions, and the findings needed to identify and disambiguate them emerge over the course of a consultation. Evaluating clinica…
The Working Set of a Coding Agent: Coherence Debt in Repository-Scale Tasks
Bardia Mohammadi, Lars Klein, Aman Chadha +2
Repository-scale coding requires an agent to keep tests, imports, configuration, and migration rules consistent within a bounded context window. We model this as reconstructing a c…
Preferred, Not Safer: Pairwise Preference Is a Poor Proxy for Clinical Safety
Fay Elhassan, David Sasu, Alexandra Kulinkina +2
We evaluate whether clinician pairwise preferences provide a reliable signal of clinical safety in large language model (LLM) evaluation using expert feedback from MOOVE (Massive O…
Ghost Tool Calls: Issue-Time Privacy for Speculative Agent Tools
Bardia Mohammadi, Lars Klein, Akhil Arora +1
Tool-augmented language agents speculatively issue likely future tool calls to hide latency, but those calls leak inferred user intent to external services before the agent commits…
Fully Open Meditron: An Auditable Pipeline for Clinical LLMs
Xavier Theimer-Lienhard, Mushtaha El-Amin, Fay Elhassan +5
Clinical decision support systems (CDSS) require scrutable, auditable pipelines that enable rigorous, reproducible validation. Yet current LLM-based CDSS remain largely opaque. Mos…
MoBayes: A Modular Bayesian Framework for Separating Reasoning from Language in Conversational Clinical Decision Support
Yusuf Kesmen, Fay Elhassan, Jiayi Ma +7
Large language models (LLMs) are increasingly used for conversational clinical decision support, yet they conflate next token prediction with probabilistic decision making. We argu…
Atomix: Timely, Transactional Tool Use for Reliable Agentic Workflows
Bardia Mohammadi, Nearchos Potamitis, Lars Klein +2
LLM agents execute multi-step workflows that mutate external state through tools. Common orchestrators treat tool return as the settlement trigger, so faults, speculation, and conc…
TiME: Tiny Monolingual Encoders for Efficient NLP Pipelines
David Schulmeister, Valentin Hartmann, Lars Klein +1
Today, a lot of research on language models is focused on large, general-purpose models. However, many NLP pipelines only require models with a well-defined, small set of capabilit…
ReasonBENCH: Benchmarking the (In)Stability of LLM Reasoning
Nearchos Potamitis, Vansh Ramani, Har Ashish Arora +3
Benchmark scores for LLM reasoning systems are reported as single numbers, yet the same model, strategy, and task can produce meaningfully different answers and costs across repeat…
Fleet of Agents: Coordinated Problem Solving with Large Language Models
Lars Klein, Nearchos Potamitis, Roland Aydin +3
While numerous frameworks have been developed to enhance the reasoning abilities of large language models (LLMs), there is a scarcity of methods that effectively balance the trade-…
Emojinize: Enriching Any Text with Emoji Translations
Lars Henning Klein, Roland Aydin, Robert West
Emoji have become ubiquitous in written communication, on the Web and beyond. They can emphasize or clarify emotions, add details to conversations, or simply serve decorative purpo…