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From the 7 of 451 papers with an AI index.

most citedTDCOSMO 2025: Cosmological constraints from strong lensing time delays

37 citations

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10 papers · 1 filter

cs.AI2026

Framework of Thoughts: A Foundation Framework for Dynamic and Optimized Reasoning based on Chains, Trees, and Graphs

Felix Fricke, Simon Malberg, Georg Groh

Prompting schemes such as Chain of Thought, Tree of Thoughts, and Graph of Thoughts can significantly enhance the reasoning capabilities of large language models. However, most exi…

cs.AI2026

Topical Phase Transitions in Artificial Intelligence Research: Large-Scale Evidence and an Early-Warning Signature for Emerging Topics

Rasul Khanbayov, Hasan Kurban

Do research topics in artificial intelligence grow gradually, or do they advance through abrupt, detectable jumps? Analyzing 80,814 accepted main-track papers from five premier AI…

cs.AI2026

Collab-REC: An LLM-based Agentic Framework for Balancing Recommendations in Tourism

Ashmi Banerjee, Adithi Satish, Fitri Nur Aisyah +3

We propose COLLAB-REC, a multi-agent framework designed to counteract popularity bias and improve diversity in tourism recommendations. In our setup, three LLM-based agents(Persona…

cs.AI20261 cited

Towards Generative Location Awareness for Disaster Response: A Probabilistic Cross-view Geolocalization Approach

Hao Li, Fabian Deuser, Wenping Yin +5

As Earth's climate changes, it is impacting disasters and extreme weather events across the planet. Record-breaking heat waves, drenching rainfalls, extreme wildfires, and widespre…

cs.AI20261 cited

Accelerating battery research with an AI interface between FINALES and Kadi4Mat

Giovanna Tosato, Leon Merker, Monika Vogler +2

The time-consuming formation process critically impacts the longevity of sodium-ion coin cells and End Of Life (EOL) performance. This study aims to optimize formation protocols fo…

cs.AI2026

Multi-Dimensional Evaluation of Sustainable City Trips with LLM-as-a-Judge and Human-in-the-Loop

Ashmi Banerjee, Adithi Satish, Wolfgang Wörndl +1

Evaluating nuanced conversational travel recommendations is challenging when human annotations are costly and standard metrics ignore stakeholder-centric goals. We study LLMs-as-Ju…