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3,243 papers
Operation Waffles proposes a harmless proof-of-concept for studying whether large language models can introduce measurable lexical drift into human language. The paper suggests using an innocuous tracer term—“waffles”—to test whether small model-level preferences for particular words, metaphors, or phrasings survive in...
Speech production integrates respiratory, laryngeal, articulatory, prosodic, linguistic and executive control, so neurodegeneration can leave measurable acoustic traces before conventional clinical scales change. Two decades of work have identified credible candidate speech and voice biomarkers for amyotrophic lateral...
Personality science compresses a person into a small readable coordinate system, and the content science of the companion papers does the analogous thing for writing, eight character axes that collapse to two interpretable dimensions, matter against manner and originality. This paper reports the coupling between those...
In-Context Signal Completion (ICSC) is presented, demonstrating that small language models fine-tuned with Group Relative Policy Optimization and physics-informed rewards can reconstruct RSSI across sequential extrapolation and spatial interpolation tasks.
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Polymer design benefits from representations that combine efficient sequence modeling with explicit access to molecular graph structure. String representations provide compact sequences but most remain sensitive to syntax and connectivity errors, whereas sequential graph generation becomes more costly as molecular grap...
Background: Recently, artificial intelligence-based tools such as large language models (LLMs) have further transformed health information-seeking practices. This study aimed to assess digital health information-seeking behaviors among healthcare professionals working in İzmir, Türkiye, and to examine individual and en...
Abstract This paper proposes a vortex bound state picture of black holes based on T3 ternary algebra (e²=1, i²=-1, ei=ie=0). Core updates in v1.4: Causal Structure Self-Consistency: V_c = c√2 is the Euclidean norm in velocity space; the axial projection is always ≤ c. The “superluminal” rotational component does not vi...
Code, pre-registrations with frozen thresholds, result summaries and manuscript for a minimal controlled model of cultural transmission in a Lewis referential game. Two small neural agents invent a language over 64 objects; each generation is a fresh pair that first learns a limited set of its parent's (object, message...
BackgroundTransgender and gender-diverse individuals experience higher mortality rates and elevated incidence of serious illness compared to cisgender populations. Despite these disparities, discrimination and stigma continue to create barriers to high-quality hospice and palliative care.AimsThis scoping review identif...
This inference originated from a conversation in which a large language model invoked knowledge from the context and integrated new concepts. It was found that after a large language model invokes existing knowledge, it does not merely copy it, but may recombine existing knowledge with other content. From this, it is i...
Abstract This paper proposes a vortex bound state picture of black holes based on T3 ternary algebra (e²=1, i²=-1, ei=ie=0). Core updates in v1.4: Causal Structure Self-Consistency: V_c = c√2 is the Euclidean norm in velocity space; the axial projection is always ≤ c. The “superluminal” rotational component does not vi...
The HCG-MLLMAD - Hierarchical Cross-Modal Grounding framework of Multimodal Large Language Model-based Anomaly Detection - a variant of the original Light-MLLMAD architecture with multi-scale visual feature pyramids, prompt routing, and a hierarchical cross-attention fusion mechanism is presented.
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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.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Learn how Google DeepMind and GovTech Singapore uses lightweight on-device Gemma models to intercept conversational scams in private chats with zero cloud data egress.
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