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From the 1 of 67 linked papers with an AI index.

collaborators

71 papers

cs.AI2026

LLM-SoccerArena: Benchmarking LLMs on Real-World Predictions in Sports

Jonas Schröder, Jonas Schweisthal, Oliver Müller +2

Large language models (LLMs) increasingly support decisions about uncertain future events, yet evaluating their ability to forecast real-world outcomes remains difficult. In partic…

cs.AI2026

AutoSynthesis: An agentic system for automated meta-analysis

Moein Taherinezhad, Sebastian Maier, Gerardo Vitagliano +2

AutoSynthesis is a multi‑agent AI system that takes a natural‑language research question and automatically conducts a full quantitative meta‑analysis, from literature search to eff…

physics.soc-ph2026

Hyperlocal monitoring of urban activity reveals responses to heat exposure

Dominique Geissler, Felix Creutzig, Ramit Debnath +1

Rising temperatures create new challenges for local heat adaptation. Yet, it remains unclear how urban activity changes during hot periods and which urban environments people conce…

cs.LG2026

Synthetic Interaction Data for Scalable Personalization in Large Language Models

Yuchen Ma, Yue Huang, Wenjie Wang +3

Personalized prompting offers large opportunities for deploying large language models (LLMs) to diverse users, yet existing prompt optimization methods primarily focus on task-leve…

cs.AI2026

Automated reproducibility assessments in the social and behavioral sciences using large language models

Tobias Holtdirk, Pietro Marcolongo, Anna Steinberg Schulten +7

Reproducibility in the social and behavioral sciences is typically evaluated by independent researchers who reanalyze the original data to assess whether the published findings can…

cs.LG2026

OncoSynth: Synthetic data generation for treatment effect estimation in oncology

Octavia-Andreea Ciora, Julian Welzel, Dennis Frauen +6

In oncology, access to patient-level data is often restricted. Synthetic data provides an alternative for analyzing treatment effectiveness, but existing methods for synthetic data…