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Focus Shifts to Structured and Verifiable AI Development

The observed trend moves beyond simple model capability improvements toward building highly reliable systems that function within complex, real-world constraints. This is evidenced by the focus on using composable architecture frameworks or subjecting AI to rigorous validation through high-difficulty benchmarks like the Ramanujan Challenge. Furthermore, securing efficiency and robustness has become a critical concern across diverse domains, from optimizing RAG performance to streamlining embedded system security patches.

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arXivJuly 29, 2026

Schrödinger's Cat: Probabilistic Representation and Prediction of Potential Scene Kinematics

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GARFIELD는 이미지와 희소한 제약 조건을 바탕으로 장면 운동학의 확률적 잠재 표현을 학습하는 새로운 모델입니다. 기존 방식보다 훨씬 빠른 속도로 미래 궤적을 샘플링하며, 움직임의 불확실성을 정교하게 모델링하여 효율적인 모션 플래닝을 가능하게 합니다.

scene-kinematics
probabilistic-modeling
motion-planning
latent-representation
video-prediction

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Focus Shifts to Structured and Verifiable AI Development

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Focus Shifts to Structured and Verifiable AI Development

Schrödinger's Cat: Probabilistic Representation and Prediction of Potential Scene Kinematics

Instruction-Tuned Models Locally Reuse Human Syntax More Than Humans Do

Re-thinking Mammography Transfer Learning: The Dataset-Informed Transfer Learning (DITL) Framework for Breast Cancer Screening and Lesion Diagnosis

Parallel Decoding Distillation for Fast Image and Video Generation

Detecting Knowledge Inconsistencies Across Text, Tables, and Knowledge Graphs

UniMem: Complementary Episodic-to-Parametric Memory for Boundary-Agnostic Task Streams

Spend Experts Where You Are Unsure: Confidence-Adaptive Routing for Mixture-of-Experts LoRA

Adversarial Comments Are Now a Vulnerability Detection Bypass Technique

HANDBOOK.md: 긴 정책(Policy)을 가진 AI 에이전트의 64%가 작업 실패

CryptanalysisBench Introduces a Framework to Measure LLM Cryptanalysis Capabilities

인공 신경망(Neural Network)의 작동 원리와 단순한 요청에서 오류가 발생하는 이유

Knowledge-Guided Multimodal Reasoning over Interacting Streams for Video-Level Ambivalence and Hesitancy Recognition

Reinforcement Learning for Code Optimization

MemLens: A Value-Aware Memory Management System with Interactive Analytics for LLM-based Agents

Does Runtime Topology Context Improve LLM-Generated Kubernetes Security Patches?

Empirical Evaluation of Out-Of-Distribution Performance of Tabular Foundation Models

Desktop-Delta Bench: Do Computer-Use Models Understand Desktop GUI Transitions?

Pictura: Perspective-View Self-Play at Scale for Driving

$π\mathbf{R}^2$: Reactive Real-time Flow Policies

Pass the Baton: Trajectory-Relayed On-Policy Distillation