AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Large audio language models (LALMs) can process speech directly, but it remains unclear how well they use the non-lexical acoustic information that speech carries. We study this question through pain, using TAME-Pain, which contains pain-neutral Harvard sentences and spoken pain ratings recorded at different self-repor...
MUSegNet reliably detected the extent of clinically significant prostate cancer on micro-ultrasound exams, paving the way for improving cancer detection for biopsy targeting and reducing inter-reader variability.
LLMs are increasingly used as automated judges for model training and evaluation, yet individual judges exhibit systematic biases that undermine reliability. Much of prior work has studied biases in pairwise LLM-as-a-judge settings; in this paper, we focus on absolute scoring tasks, which mirror more realistic use case...
Traditional large language models (LLMs) are scoped to individual user sessions, limiting their knowledge to a single conversation and preventing them from learning user preferences that evolve over time. Existing agentic memory systems address this limitation but generally operate at the individual-user level, restric...
Metag is a dataset to accelerate the development of meta-reviewing agents, specifically to identify changes made to scientific articles during the review-rebuttal process and will enable building methods to empower meta reviewers to quickly identify whether authors have addressed reviewer statements and where in the pa...
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