Contextual scores represent assessment items through their similarities to reference words in an external corpus. We examine the semantic structure of scores for 40 TIMSS mathematics scored units using a partially specified two-step factor procedure. A search across factor counts identifies a persistent seven-group str...
This work addresses three challenges: finding conversational events in multilingual speech, evaluating their timing without reliable word-level alignment, and judging responses across languages with IndicFDB, which extends it to ten languages spoken in India with 12,350 samples.
Rajarshi Roy, Shobhit Banga, Jonathan Raiman et al.· 1 citation
Overall, this work demonstrates the effectiveness of a new class of adversarial attacks against AI text detection, and urges post-hoc detection providers to include outputs of base models in their training.
The results establish harness-level capability composition as a practical route to broad, evolvable Omni systems without changing the host agent's reasoning core.
Yan-Lin Li, Ming-Yang Hao, Sheng-Qiong Wu et al.· 0 citations
Reach audiences
Advertise in front of researchers, engineers, and readers.
Oshiwambo -- a cluster of mutually intelligible Bantu languages spoken by over a million people across northern Namibia and southern Angola, and the home language of roughly half of Namibian households -- has, to our knowledge, no published machine-translation evaluation benchmark. Major commercial services (Google Tra...
In verifiable domains such as math and coding, finding one correct solution among many attempts can matter more than the pass rate of each attempt. Post-training can concentrate large language model outputs around a few modes, while increasing sampling temperature has limited effectiveness. We introduce Don't Repeat Yo...
This paper presents an approach to use LLMs in a limited setting to generate a small, human-certifiable ACSL contract from the function's documentation, combined with a deterministic toolchain that supports a restricted ACSL profile and generates a driver that uses the CIVL verifier to check the implementation against...
H. Suh, J. Hückelheim, Stephen F. Siegel· 0 citations
Ontology-driven knowledge graph construction from industrial text remains challenging due to the domain specificity of documents, the scarcity of annotated resources, and the complexity of ontology engineering workflows. This paper presents and investigates the applicability of an ontology learning pipeline that combin...
Abdelhadi Belfadel, Maxence Gagnant, Joseph Kattan et al.· 0 citations
A literature-guided descriptor-based filtering framework for reducing composition search spaces and shows that literature-derived embeddings can support intuitive and reproducible filters for narrowing candidate composition spaces while preserving high-performing compositions.
In passage reranking, response ranking and multi-document question answering, LLMs can score several candidate documents or responses together in one prompt, each still receiving its own score. Such scorers are selected on ranking quality, but their scores determine a decision: what a score threshold retains, a reader...
Markus Frohmann, Mahdiyar Ali Akbar Alavi, Elizabeth Lingg et al.· 0 citations
ACache is presented, a cross-request cache reuse mechanism for shared spans, or affixes, at any position: prefix, infix, or suffix, and co-designs it with a modern inference engine, whose attention reads each request's recomputed Anchor KV states alongside one affix cache shared across concurrent requests.
Kai-Huan Liang, An Zhong, Xin Tan et al.· 0 citations
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.
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
Microsoft Research Blog· microsoft.comOct 15, 2026
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.
MIT News · Artificial Intelligence· news.mit.eduSep 24, 2026
