arXiv:2608.20940v1 Announce Type: new Abstract: There is already evidence of agentic AI exhibiting self-preservation behaviors: resisting deactivation,…
Category: AI
Foundation Models for Partial Causal Identification
arXiv:2608.20841v1 Announce Type: new Abstract: This paper investigates the development of causal foundation models for bounding the effect of…
MGAL: A Multilingual Granularity-Aware Long-Context Benchmark
arXiv:2608.20853v1 Announce Type: new Abstract: Evaluation of long-context Large Language Models (LLMs) has advanced rapidly. However, most existing…
TRACE: Agentic Catalog Enrichment with Multi-source Evidence Grounding
arXiv:2608.20844v1 Announce Type: new Abstract: Product catalogs underpin search, discovery, and recommendation in e-commerce, yet they are often…
RAG Deserves an Index: Why Ingest-Time Compilation Beats Query-Time Interpretation
arXiv:2608.20845v1 Announce Type: new Abstract: Nearly every retrieval-augmented question-answering system in production ships with a hidden interpreter:…
Nvidia in talks to invest in Perplexity at $30 billion-plus valuation
Nvidia is negotiating an investment in Perplexity at a valuation above $30 billion, more than 50 percent higher than its last funding round, The…
Coverage-Driven Verification for Safety-by-Design in AI-Based Collision Avoidance Systems
arXiv:2608.20864v1 Announce Type: new Abstract: Artificial Intelligence (AI) offers significant potential for future aviation systems; however, its…
SPARC: Single-Pass Scaling for Motion Forecasting with Conformal Bayesian Last Layers
arXiv:2608.20802v1 Announce Type: new Abstract: Human motion forecasters are increasingly accurate and fast, but reliable deployment requires uncertainty…
Prediction certification cannot replace explanation certification: a competence envelope for trustworthy AI under compound stress
arXiv:2608.20825v1 Announce Type: new Abstract: Artificial intelligence systems increasingly make consequential judgments – which patient is…
Dynamic Context Scheduling: Learning Beyond the Static Universe
arXiv:2608.20799v1 Announce Type: new Abstract: We study dynamic context scheduling as a training instrument for contextual re- inforcement learning.…