Input-conditioned neural interventions raise a runtime question: what persists when one behavioral specification admits multiple actions whose validity depends on execution state? We introduce replay-gated neural execution, separating five objects: a persistent behavioral predicate, its state-indexed certified realizat...
We present H2LooP Telecom Model v1, a domain-specialized large language models fine-tuned for the telecommunications industry. We release two domain-adapted model variants serving complementary use cases: a comprehension-focused variant for telecom domain question answering and reasoning, and an agentic variant for aut...
Amit Singh, Vedant Nipane, Mayank Goel et al.· 0 citations
Ambient AI is increasingly adopted in healthcare to automatically generate clinical notes from patient-clinician conversations, with the potential to substantially reduce clinician documentation burden. However, generated notes may omit clinically relevant information discussed during the encounter, creating informatio...
Jakir Hossain, Yi-Fei Zhao, Hongjian Wang et al.· 0 citations
BizSage is presented, a multi-agent framework combining corpus-level fine-grained retrieval with quality-driven self-evolution that paves the way for reliable research assistance in economics, business, and the broader social sciences.
Yu-He Wu, Guang-Yu Wang, Jia-Xin Liu et al.· 0 citations
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Long-horizon interactions with LLM-based assistants require memory systems that preserve and update user states, preferences, and interaction histories. Existing evaluations report end-to-end QA accuracy and cannot determine whether errors arise from encoding, retrieval, or generation. We introduce EvalMem, an operatio...
Ze-Yu Liu, Jian-Yuan Zhong, Rong-Duo Han et al.· 0 citations
Large language models (LLMs) can generate fluent and coherent text that is increasingly difficult to distinguish from human writing, motivating the development of automatic AI-generated text detectors. However, the robustness of such detectors under adversarial generation remains uncertain. This paper presents SHADE (S...
Antonela Tommasel, Juan Manuel Rodriguez· 1 citation
Long multilingual conversational spoken question answering requires systems to balance long-range transcript semantics with sparse acoustic and speaker-sensitive cues. We present the Bairong system for the MLC-SLM 2026 Challenge, where a diarization-ASR front-end produces speaker-attributed transcripts and a dynamic ev...
Shang-Kun Huang, Jun-Chao Hu, Hua Shen et al.· 2nd Workshop on Multilingual...· 1 citation
SCoP (Structured Constraint Parsing), a constraint-centric framework that externalizes temporal decisions before answer inference, separates answer-seeking event patterns from temporal anchor events, conservatively grounds them to canonical TKG entities and relations, and translates temporal intent into executable cons...
Xiao-Kun Guo, Zhen Xu, Dongdong Huo et al.· 0 citations
SALSA (Semi-Autonomous Literature Summarization Assistant) is an open- source, human-in-the-loop platform for extracting structured scientific datasets from multimodal literature sources. The software combines document parsing, large language models, optical character recognition, computer vision, figure digitization,...
William Schertzer, Sonakshi Gupta, R. Ramprasad· 0 citations
This exploratory pilot study evaluates the scope and perceived accuracy of personal information output from ongoing conversational interactions in generative AI systems using GPT-5.2 Instant and GPT-5.2 Thinking, categorized into three output types: Fact, Inference, and Confidence. Based on the evaluation results obtai...
This work introduces PII-Tracer, a compact 0.6B-parameter detector trained with conversation-level supervision that attains the highest entity-level coverage of any system the authors evaluate and also performs strongly on standard single-record benchmarks.
Kai-Yuan Zhang, Chuan Wang, Joey Zhong et al.· 0 citations
It is found that following LLM supply shocks, unverified reviews shift toward greater negativity: more 1-stars, fewer 5-stars, and lower ratings, suggesting that strategic AI use may reshape platform competition dynamics.
Valeria Lermana, Oren Rigbi, Y. Dover· CESifo working papers· 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.
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