A Bayesian Mirror Architecture for Emergent Consciousness: Circular Hierarchies, Self-Manifolds, and Hybrid Event-Self Binding
arXiv:2610.08792v1 Announce Type: new
Abstract: We present a foundational formulation of the Bayesian Mirror Architecture (BMA), a self-referential generative framework in which sensory abstractions, meta-abstractions, and a self-latent interact through circular recursion. The defining constraint i...
Beyond Baseline Severity: Temporal and Disease-Specific Predictors of Depression Outcomes Following Mindfulness Interventions
arXiv:2610.08809v1 Announce Type: new
Abstract: Depression severity among patients with chronic or acute medical conditions is influenced by a complex interaction of baseline psychological state, demographic characteristics, clinical context, and engagement with behavioral interventions. This paper...
Transferability and operational reliability of a Prithvi crop classification foundation model under phenological and geographic shift across three continents
arXiv:2610.08810v1 Announce Type: new
Abstract: Fine-tuned geospatial foundation models (GeoFMs) pretrained on large satellite archives have been shown to improve crop classification accuracy and geographic transferability. However, their operational performance beyond the training distribution rem...
KVFetch: Temporal Prefetching for the Missing Half of KV Cache Compression
arXiv:2610.08811v1 Announce Type: new
Abstract: As context windows scale to tens or hundreds of thousands of tokens, KV cache compression has become essential for efficient LLM inference. Existing methods fall into three families: score-based eviction, summary compensation, and offload-and-recall. ...
Adaptive Workflow Intelligence: A Cognitive Architecture for Context-Driven Enterprise Automation
arXiv:2610.08793v1 Announce Type: new
Abstract: Enterprise systems increasingly rely on automated workflows, yet many AI-driven solutions remain brittle under non-stationary conditions, evolving policies, and delayed operational feedback. While reinforcement learning and large language model (LLM) ...
Route-Verify-Vote: Procedure-Conditioned Self-Consistency for Mixed-Domain Reasoning
arXiv:2610.08814v1 Announce Type: new
Abstract: Compositional generalization remains challenging when language models must combine familiar reasoning operations in unfamiliar ways. The Scenario-Based Commonsense Reasoning Evaluation (SCoRE) 2026 tests this ability on three mixed domains absent from...
How Could AI Eliminate Humanity? A Failure-Mode Analysis of Civilizational Risk
arXiv:2610.08878v1 Announce Type: new
Abstract: This article develops a failure-mode framework for analyzing how advanced artificial intelligence could contribute to human extinction, irreversible civilizational collapse, or permanent human disempowerment. The central thesis is that catastrophic AI...
Diffusion-based models decompose sampling into many small Gaussian denoising steps, an assumption that breaks down when generation is compressed to a few coarse transitions. Existing few-step methods address this through distillation, consistency training, or adversarial objectives, but sacrifice th...
Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses
Training AI agents with reinforcement learning can be challenging because their tools, context, and decision-making are managed by complex frameworks. Agent Lightning connects existing agents to RL training, making it easier to improve them without rebuilding them.
The post Agent Lightning v1.0: A 3...
7 reasons small language models belong in your 2027 AI roadmap
A frontier model reformatting JSON is expensive overkill. Here are seven sourced reasons small language models earn a place in your 2027 roadmap, and how to start.
Text2Dashboard: A Governed Agent Architecture for Natural-Language Dashboard Generation over Enterprise DataBrain
arXiv:2610.06914v1 Announce Type: new
Abstract: Text2Dashboard is a DataBrain-specific prototype that turns natural-language analytic requests into inspectable dashboards. An installable Codex plugin and standalone Agent Runtime combine schema-constrained model decisions with typed tools, persisten...
TEMPEST: Temporal Embeddings for Scalable Driver Identification via Angular Margin Learning
arXiv:2610.06855v1 Announce Type: new
Abstract: Scalable driver identification requires embedding models that maintain discriminative performance as fleet size grows, yet existing triplet-loss formulations degrade rapidly with driver pool size and overfit to session-specific patterns under rigorous...
When Does External Guidance Help LLM Reasoning? A Bias-Variance Theory of Guidance-Augmented GRPO
arXiv:2610.06861v1 Announce Type: new
Abstract: Reinforcement learning with verifiable rewards (RLVR) has become the dominant paradigm for eliciting multi-step reasoning in large language models, and a recent wave of methods (LUFFY, ExPO, PAPO, TAPO) further augments RL with \emph{external guidance...
Neutrosophic Ensemble Classification for Uncertainty-Aware Bearing Fault Detection: Evidence from Laboratory and Variable-Speed Industrial Benchmarks
arXiv:2610.06880v1 Announce Type: new
Abstract: Machine learning classifiers for bearing fault detection produce scalar confidence scores that conflate confident errors with genuinely ambiguous predictions, and the conventional truth/falsity pair (F = 1 - T) is algebraically redundant by constructi...
RadOnc-Agent: An LLM-Orchestrated Framework for AI Workflows Across the Radiotherapy Care Pathway
arXiv:2610.06923v1 Announce Type: new
Abstract: Artificial intelligence has advanced individual radiotherapy tasks, yet these capabilities remain separated across clinical stages, software environments and data modalities. This fragmentation contrasts with the longitudinal radiotherapy workflow fro...
GAMEGO: Training Game-Dev Agents with Synthetic Trajectories Anchored in Real-World Assets
arXiv:2610.06910v1 Announce Type: new
Abstract: Recent advances in Large Language Models (LLMs) have demonstrated remarkable capabilities in web front-end execution, with browser-based game generation emerging as a particularly prominent frontier. While previous efforts frequently rely on complex m...
FluidPD: In-Place Elasticity for SLO-Aware Prefill-Decode Disaggregated LLM Serving
arXiv:2610.06917v1 Announce Type: new
Abstract: Prefill-decode disaggregation is becoming a common architecture for LLM serving because it separates two phases with distinct execution patterns and SLO objectives. Existing systems typically combine a fixed prefill/decode worker ratio with request ro...
6 questions that expose agent washing in any AI vendor demo
Vendor demos are rehearsed performances. Production is improv night with a hostile crowd. These six questions reveal whether an AI agent can reason, escalate, and hold up on your own messy data before the procurement paperwork lands.
Proxy Confidence: Auditing Black-Box LLM Agents with a Surrogate's Log-Probabilities
arXiv:2610.03894v1 Announce Type: new
Abstract: A deployed LLM agent emits tool calls, queries, and code that can be silently wrong -- by the time the error surfaces, the action has run. Frontier chat APIs hide the model's token probabilities; the agent's stated confidence barely beats chance on th...
REACT: Physically and Chemically Consistent Reconstruction of Marine Active Tracers
arXiv:2610.03888v1 Announce Type: new
Abstract: Reconstructing global sea surface pH from sparse observations is critical for monitoring ocean acidification and understanding marine carbon cycling. Traditional assimilation and inverse models are physically grounded but costly for large-scale recons...