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8,786 papers
This work introduces a reliable evaluation approach for DDG, based on newly proposed evaluation criteria and powered by an LLM-as-a-judge, and proposes an LLM-based LDDG approach that employs iterative simplification.
We study false-alert control when screening for text generated by artificial intelligence (AI). The screening procedure selects document prefixes and detectors from observed evidence and may stop before exhausting its inspection budget. We give two finite-sample constructions under document-level exchangeability betwee...
A statistical specification for whether valence among the users who write reviews of an app has changed enough to warrant investigation of a release, outage, or support issue is proposed, applied to written Google Play reviews collected under a declared locale, language, sort order, retrieval cap, and window rule.
This work highlights the need to audit feature transferability and report worst-case domain robustness in cognitive speech screening by proposing a fusion method that integrates XLM-R text baseline scores with evidence anchors selected during training.
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The Cross-Backend Quantum Inspired Evolutionary Optimizer (QIEO) is presented, the runtime core of BQP's BQPhy solver, which addresses the gap between algorithmic performance and hardware portability through a single-source-of-truth architecture.
The proposed symbiotic architecture employs an injector module that writes audio-conditioned vectors directly into the target LLM's short-term memory, enabling the LLM to behave as an audio language model (ALM) and improves the scalability of ALMs.
A detection framework that models this attack chain by combining a text detector, verifiers specific to each stage, explicit rule-based risk signals, user intent and action consistency analysis, and a logistic decision policy is proposed, which achieves a mean F1 score under the strict threshold setting policy.
The Epstein Files Engine, an A.I. agent The New York Times deployed to investigate Jeffrey Epstein's files, is described and it is argued that newsroom agents serve newsrooms best not as autonomous writers, but as interfaces to source material and institutional knowledge.
The results provide compelling evidence that the CLAP score and related metrics do not capture fine-grained musical meaning or attribute bindings; their representation is closer to a bag-of-words that leaves them insensitive to meaning-changing perturbations of the caption.
Oracle analysis shows that substantially larger WER reductions are possible through utterance-level scale selection and identifies how beneficial adjustments vary with domain shifts.
This work investigates strategic diversity, or substantive variation among approaches to a problem, as an alternative principle for constructing self-training data with two sampling methods: GROOT, a new method which constructs a hierarchical tree of approaches and samples distinct paths, and Verbalized Sampling, adapt...
Ensuring online safety through content monitoring had raised Hate Speech Detection as a crucial task to be addressed. By essence the task demands the capture of contextual cues, which are essential for a precise understanding of the content's intent. Although automated detection approaches for the task have advanced si...
Flint-interactive gives AI agents a language for creating interactive visualizations. Click a chart, filter data, highlight related content, and explore beyond the view the author originally chose. The post Flint-interactive: A language for creating interactive data visualizations appeared first on Microsoft Research.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.
A new language-processing tool could help identify the highest-risk individuals from natural language, enabling swifter interventions.
A Blog post by Liquid AI on Hugging Face
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