論文・研究の記事
Estimating suicide risk from text
A new language-processing tool could help identify the highest-risk individuals from natural language, enabling swifter interventions.
Introducing Gemini 3.8 Live with Live Avatar
What Changes When Fact-Verification Scores Improve? Evidence and Answer Accounting Across Trained Verifiers and LLMs
arXiv:2609.27064v1 Announce Type: new Abstract: A joint fact-verification score assesses answers and submitted evidence together. When the score improves, how much of the gain remains if the answers are held fixed? On F…
LexLattice: Multilingual Extractive Summarization via Neural Cellular Automata on Document Hierarchies
arXiv:2609.27032v1 Announce Type: new Abstract: Faithfulness is a central concern in legal text summarization, which motivates extractive approaches that select verbatim content traceable to its source. Such methods typ…
The Illinois Social Attitudes Aggregate Corpus (ISAAC): An Open Tool and Reproducible Pipeline for Analyzing Social Group Discourse at Scale
arXiv:2609.27059v1 Announce Type: new Abstract: We introduce the Illinois Social Attitudes Aggregate Corpus (ISAAC), an open, modular, and accessible corpus of 527 million+ English-language Reddit posts selected for rel…
COMED: The Missing Middle Between Routing and Collaboration in Multi-LLM Inference
arXiv:2609.26913v1 Announce Type: new Abstract: No single Large Language Model (LLM) is uniformly reliable across queries, motivating multi-model inference systems that either route among models or combine their outputs…
Recognized but Not Produced: A Generation Benchmark for Culturally Specific Kinship Terms
arXiv:2609.26942v1 Announce Type: new Abstract: Current literature evaluates large language models (LLMs) on multilingual kinship understanding using multiple choice benchmarks, treating it as a recognition problem. We…
Experts Rise Where LLMs Disagree: Using Cross-Model Disagreement to Target Expert Effort in LLM Codebook Revision for Large-Scale Annotation
arXiv:2609.26926v1 Announce Type: new Abstract: Large-scale text annotation brings expert insight to millions of documents, often through a codebook that AI annotators follow. Developing a robust codebook, however, take…
MedGate-Fusion: Integrating First-Encounter Semantic Narratives and Physiological Biomarkers for Prospective Stroke Risk Stratification
arXiv:2609.25272v1 Announce Type: new Abstract: Prospective stroke risk stratification in primary care is challenging because early risk signals are distributed across routine biomarkers and unstructured clinical narrat…
The AI Neuroscientist: An Interactive Agentic Interface for Neuroimaging Analysis
arXiv:2609.25254v1 Announce Type: new Abstract: Analyzing neuroimaging data requires specialized coding and statistical expertise, which limits accessibility for researchers without computational backgrounds. We present…
When LLM Agents Fail to Read the Room: ReAdapt for Relational Social Reasoning
arXiv:2609.25284v1 Announce Type: new Abstract: A social agent's most basic decisions (should I react to this post? who should I reach out to?) are not purely content problems. The right action often hinges on the laten…
X-Planner: Event-Structured Task Planning for Embodied Intelligence
arXiv:2609.25187v1 Announce Type: new Abstract: Task planning bridges high-level instructions and executable behavior in long-horizon manipulation, yet modern Vision-Language-Action (VLA) systems often leave this interm…
Do Synthetic Personas Predict Real Audience Response? A Sim-to-Real Study Where a No-Persona Baseline Beats Persona-Based Copy Simulation
arXiv:2609.25010v1 Announce Type: new Abstract: Marketers increasingly use large language models (LLMs) as "synthetic personas" to predict how an audience will react to a piece of copy before it ships, encouraged by evi…
Do Existing Preconditioners Improve Biomedical Tabular Foundation Learning? An Empirical Study on TabPFN Optimization
arXiv:2609.25013v1 Announce Type: new Abstract: Tabular foundation models have recently shown strong potential for structured biomedical data analysis. Among them, TabPFN has emerged as an effective approach for low-dat…
Lean Pool: An AI-Maintained Archive of Formalized Mathematics
arXiv:2609.25199v1 Announce Type: new Abstract: Lean Pool is a repository of formalized mathematics. It is grown, maintained and optimized by AI agents.
EduBehaviors: Assertion-based Schemas for Auditable Coding of Educational Dialogues
arXiv:2609.27043v1 Announce Type: new Abstract: Large language models have allowed the rapid deployment of pedagogical annotations corresponding to constructs of interest, allowing a natural language interface for gener…
Ovis-Embedding: Pushing the Frontiers of Universal Omni-Modal Embeddings
arXiv:2609.25165v1 Announce Type: new Abstract: In this report, we introduce \textbf{Ovis-Embedding}, a state-of-the-art omni-modal embedding family built on native integration of text, image, video, and audio. Instead…
The promise and peril of using visual AI to study cities
In their new book, “How AI Sees the City,” the leaders of MIT’s Senseable City Lab examine the technology’s implications for researching urban life.
LEGO: Synergizing Expert GraphRAG and Expert Chain-of-Thought for Legal Reasoning
arXiv:2609.27009v1 Announce Type: new Abstract: Large language models are increasingly applied to high-risk domains such as law, yet complex legal reasoning remains limited by two structural challenges. First, existing…
Classifying Interpretive Canons at the Sentence Level: A Benchmark from the German Federal Constitutional Court
arXiv:2609.26945v1 Announce Type: new Abstract: Judicial reasoning remains challenging for large language models (LLMs) to analyze. This paper contributes a sentence-level benchmark for evaluating the ability of LLMs to…
An Accurate and Interpretable Hyper Graph Neural Network for GBM Survival Prediction
arXiv:2609.25088v1 Announce Type: new Abstract: Survival prediction for glioblastoma multiforme (GBM) demands models that are both accurate and interpretable, yet existing approaches treat these objectives as com- petin…
4DGS-JEPA: Temporally Compositional Joint-Embedding Prediction for Dynamic Gaussian Splatting
arXiv:2609.25036v1 Announce Type: new Abstract: Dynamic Gaussian Splatting provides an explicit representation of evolving 3D scenes, but existing approaches are primarily optimized for reconstruction, future-state gene…
When Learned Context Planning Fails to Beat Strong Retrieval: A Controlled Study of Planning, Routing, and Reranking for Long-Context QA
arXiv:2609.26976v1 Announce Type: new Abstract: Learned context planning selects evidence atoms before an answer model reasons over them. We test whether this learned selection improves long-context multiple-choice QA a…
MIRI’s Position on the Ban Artificial Superintelligence Act of 2026
By Aaron Scher; endorsed by Bourgon, Soares, and Yudkowsky on behalf of MIRI. MIRI has been warning about the extinction threat from superintelligent AI for over two decades. Only recently has this danger become known i…