LLM judges now score outputs against rubrics, in benchmarks and as training rewards. Decision models return probabilities over permitted answers with a confidence score but no free text. Two such models are Jev and an open reproduction, Perplexity's Decider. We compare each with three flash-tier LLM judges on nine pane...
D. Rao, Christopher Callison-Burch· 7 citations· ⚡1
It is suggested that a cascade of judges succeeds only when its judges make complementary errors, and that future decision models should be designed afresh with that aim.
D. Rao, Christopher Callison-Burch· 7 citations· ⚡1
Systematic reviews underpin clinical guidelines, yet their data-extraction step is a major expert-labor bottleneck bound by a protocolized workflow: two reviewers extract each study independently, an adjudicator resolves disagreements, and the team keeps an auditable record of how every value was produced. Large langua...
S. Kosuri, A. Bhosale, M. Glick et al.· 0 citations
The Media Bias Detector is introduced, a scalable computational framework that integrates large language models (LLMs) with near-real-time news scraping to extract structured annotations, including political lean, tone, topics, article type, and major events, across hundreds of articles per day.
Samar Haider, Amir Tohidi, Jenny S. Wang et al.· Science Advances· 0 citations
PersonaMem-v3 is introduced, a real-world-grounded benchmark and evaluation harness for omni-platform personal intelligence that evaluates whether AI agents can infer holistic user understanding from cross-platform evidence, personalize responses, rerank recommendations on social media, follow user steering through nat...
Bo-Wen Jiang, Yuan Yuan, Zhuo-Qun Hao et al.· 0 citations
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