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5月25日、内閣総理大臣官邸で開催された車座対談に、Sakana AIの伊藤錬が参加しました。金融など各産業に特化した高度なAI実装の実例をご紹介しました。また、海外の先端モデルも活用しつつ、日本独自の技術で、我が国の防衛の自律性やデータ主権を確保する具体的方法についても高市総…

5月25日、内閣総理大臣官邸で開催された車座対談に、Sakana AIの伊藤錬が参加しました。金融など各産業に特化した高度なAI実装の実例をご紹介しました。また、海外の先端モデルも活用しつつ、日本独自の技術で、我が国の防衛の自律性やデータ主権を確保する具体的方法についても高市総理と貴重な意見交換の機会をいただきました。本日、スタートアップ４社（Atomis、Sakana AI、Oceanic

researchdavid-ha--x

25 May 2026

Search: “research”

TUBE: Tangent Upper Bound on Evidence for Discrete Diffusion Language Models

Turn-Based Structural Triggers: Prompt-Free Backdoors in Multi-Turn LLMs

Uncovering Autoregressive LLM Knowledge of Thematic Fit in Event Representation

Uncovering Vulnerabilities of LLM-Assisted Cyber Threat Intelligence

Understanding, Accelerating, and Improving MeanFlow Training

Understanding the Impact of Geometric Foundation Models on Vision-Language-Action Models

Universal Activation Verbalizer: A Unified Framework for Cross-Model Activation Explanation

Variable Clustering via Distributionally Robust Nodewise Regression

Verified SHAP: Provable Bounds for Exact Shapley Values of Neural Networks

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints

Voting with the Graph: Stable RLAIF via Topological Consistency Maximization

What Questions Should Robots Be Able to Answer? A Dataset of User Questions for Explainable Robotics

When Does Synthetic Patent Data Help? Volume-Fidelity Trade-offs in Low-Resource Multi-Label Classification

When Gradients Collide: Failure Modes of Multi-Objective Prompt Optimization for LLM Judges

When In-Distribution Gains Fail: Evaluating Weak-to-Strong Reward Models under Preference Shift

Which Is Better For Reducing Outdated and Vulnerable Dependencies: Pinning or Floating?

WINO: A Weak-Form Physics Informed Neural Operator for Hyperelasticity on Variable Domains

Word Class Representations Spontaneously Emerge from Successor Representations Trained on Natural Language

WTKO-CNN: Deep Learning Reveals Sequence Motifs Distinguishing Wild-Type and Knockout ATAC-seq Peaks

You Can Ground Earlier than See: An Effective and Efficient Pipeline for Temporal Sentence Grounding in Compressed Videos

Zero-Shot Parkinson's Disease Detection from Speech: Comparing Large Audio and Language Models

Zeroth-Order Nonconvex Nonsmooth Optimization with Heavy-Tailed Noise

A comprehensive evaluation of pretraining strategies for channel-agnostic contrastive self-supervision of biosignals

A drone-based framework for coral habitat mapping via weakly supervised segmentation

A Fine-Tuned BERT Classifier for Personal-Letter Titles in Late-Ming and Early-Qing Collected Works

A graph-based analysis of semantic types and coercion in contextualized word embeddings

A Simple Plug-in for Improving Eviction-Based KV Cache Compression

A solution to generalized learning from small training sets found in infant repeated visual experiences of individual objects

A Survey of Text and Speech Resources for Hausa and Fongbe: Availability, Quality, and Gaps for NLP Development

Accelerating ground state search of spatial photonic Ising machines with genetic-simulated annealing hybrid algorithm

Active Sensing Subserves Task-Level Control

Adaptive Mass-Segmented KV Compression for Long-Context Reasoning

Adversarial Vulnerability Under Temporal Concept Drift: A Longitudinal Study of Android Malware Detection

AGZO: Activation-Guided Zeroth-Order Optimization for LLM Fine-Tuning

AI-Friendly LaTeX: Using LaTeX Code as a Knowledge Source for Retrieval-Augmented Generation

Amortized Simulation-Based Inference in Generalized Bayes via Neural Posterior Estimation

An AI-Driven Framework for Energy-Efficient Environmental Monitoring in Smart Cities Using Edge Intelligence

Any-Dimensional Invariant Universality

ArcMark: Distortion-Free Multi-Byte LLM Watermark via Optimal Transport

Are Targeted Data Poisoning Attacks as Effective as We Think?

Asymmetric Scaling Laws from Sparse Features

Automatic Construction of Clinical Scoring Systems with LLM Agents

Benchmarking Gaslighting Attacks Against Speech Large Language Models

Beyond Log Likelihood: Probability-Based Objectives for Supervised Fine-Tuning across the Model Capability Continuum

Calibration-Informative Region Selection for Online LiDAR--Camera Calibration in Agricultural Environments

Call for Papers - Workshop on Unlearning and Model Editing U&ME at ECCV 2026 [R]

Cascaded Transfer: Learning Many Tasks under Budget Constraints