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A Pipeline for Generating Longitudinal Synthetic Clinical Notes Using Large Language Models This paper introduces a new method for creating synthetic clinica...
Root cause analysis (RCA) is a critical task for LLM agents, requiring them to pinpoint the source of failures in complex, interconnected software systems.
When Does Combining Language Models Help? A Co-Failure Ceiling on Routing, Voting, and Mixture-of-Agents Across 67 Frontier Models This paper investigates th...
Simulation-based inference for rapid Bayesian parameter estimation in epidemiological models: a comparison with MCMC Mechanistic epidemiological models are e...
Einstein World Models (EWMs) are a new framework designed to improve how Large Language Models (LLMs) perform complex reasoning.
Look-Before-Move: Narrative-Grounded World Visual Attention in Dynamic 3D Story Worlds introduces a new framework for camera planning in 3D environments.
KARLA: Knowledge-base Augmented Retrieval for Language Models The paper introduces KARLA, a new method designed to improve how Large Language Models (LLMs) a...
Generative Retrieval via Diffusion Transformer with Metric-Ordered Sequence Training and Hybrid-Policy Preference Optimization This paper addresses a common...
Evaluating the output of Large Language Models (LLMs) is a significant challenge. Traditional automated metrics often fail to capture the nuance of human lan...
Diagnosing Task Insensitivity in Language Agents explores why large language models (LLMs) often struggle to generalize to new, out-of-distribution tasks des...
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