Large Language Models
Entity.
- Evidence
- 1,090 documents · 246 separate publishers
- Standing
- A name from our starting list; its record is kept up to date automatically from coverage
- Time
- first seen 20 Mar 2026, last seen 11 Nov 2026
- Measured
- 1% of mentions say something specific about it; the rest only name it
- As of
- 12 Nov 2026
Where this comes from
- PreventionWeb (UNDRR) · 2026-11-09 · Classifying perceived shaking in post-earthquake social media with large language models for rapid estimation of seismic intensity-affected areas (opens the source in a new tab)
- ArXiv cs.AI · 2026-11-06 · Benchmarking Large Language Models on Heterogeneous Cognitive and Biomedical Knowledge Graphs: The Role of Graph Grounding in Multi-Hop Reasoning and Hallucination Mitigati… (opens the source in a new tab)
- arXiv cs.AI · 2026-10-31 · Post-Training Large Language Models with LLMON (opens the source in a new tab)
- awwa.org · 2026-10-30 · Large language models are a tool, not a replacement, for utility communications (opens the source in a new tab)
- 2 Minute Medicine · 2026-10-29 · Care recommendations by large language models were associated with higher healthcare costs (opens the source in a new tab)
- arXiv cs.AI · 2026-10-19 · Trapped in Your Story: Evaluating Narrative-Induced Sycophancy in Large Language Models (opens the source in a new tab)
- arXiv cs.AI · 2026-10-13 · Let Large Language Models Judge Each Other: Multi-Agent Peer-Reviewed Reasoning for Medical Question Answering (opens the source in a new tab)
- PreventionWeb (UNDRR) · 2026-10-07 · Global flood research patterns, disparities, and risk–attention mismatches revealed by large language models (opens the source in a new tab)
- Jedi-Knowledge · 2026-10-07 · Benchmarking the Personalization Capabilities of Large Language Models (opens the source in a new tab)
- Jedi-Knowledge · 2026-09-28 · A Survey on Fake Review Detection: From Pre-trained Language Models to Large Language Models (opens the source in a new tab)
- arxiv.org · 2026-09-18 · Safety Beyond the Interface: Detecting Harm via Latent States in Large Language Models (opens the source in a new tab)