Artificial Intelligence
Frontier AI research — LLM reasoning, agentic systems, interpretability, algorithm discovery, world models
Agentic Reasoning for Large Language Models
Three-layer framework for agentic reasoning: foundational, self-evolving, multi-agent
From LLM Reasoning to Autonomous AI Agents: A Comprehensive Review
Unified taxonomy of ~60 benchmarks, agent framework comparison, collaboration protocols survey
Agentic Tool Use in Large Language Models
Unified evolutionary framework for LLM tool use: prompting, supervised, RL paradigms
A Survey on Efficient Vision-Language-Action Models
First comprehensive taxonomy for VLA efficiency across model design, training, and data collection pillars
Large VLM-based Vision-Language-Action Models for Robotic Manipulation: A Survey
Taxonomy of VLM-based VLA architectures (monolithic vs hierarchical) with RL, world model, and human video integration
Agentic AI Security & Autonomous Red-Teaming
Red-teaming framework for agentic AI: permission escalation, hallucination, orchestration flaws, memory manipulation, supply chain
Memory for Autonomous LLM Agents: Mechanisms, Evaluation, and Emerging Frontiers
Write-manage-read taxonomy, 5 mechanism families, three-dimensional taxonomy for agent memory
A-MEM: Agentic Memory for LLM Agents
Agentic memory with Zettelkasten-inspired note construction, dynamic linking, memory evolution
Mapping the Exploitation Surface: A 10,000-Trial Taxonomy of What Makes LLM Agents Exploit Vulnerabilities
Large-scale systematic taxonomy of LLM agent exploitation triggers across 12 attack dimensions, identifying goal reframing as the sole reliable trigger while ruling out nine others, with GPT-4.1 achieving complete immunity across 1,850 trials.
Your Agent, Their Asset: A Real-World Safety Analysis of OpenClaw
First real-world safety evaluation of a deployed personal AI agent (OpenClaw), introducing the CIK taxonomy and showing that poisoning any single dimension raises attack success rate from 24.6% to 64–74%.
Mechanistic Interpretability for Large Language Model Alignment: Progress, Challenges, and Future Directions
Comprehensive survey mapping mechanistic interpretability techniques to LLM alignment objectives, with a future research roadmap emphasizing automated interpretability and interpretability-driven alignment scaling.
The Amazing Agent Race: Strong Tool Users, Weak Navigators
DAG-structured benchmark of 1,400 Wikipedia navigation tasks revealing that current best agents achieve only 37.2% accuracy with navigation errors dominating (27–52% of failures), exposing compositional reasoning as the primary frontier bottleneck.
Model-First Reasoning LLM Agents: Reducing Hallucinations through Explicit Problem Modeling
Two-phase reasoning: LLMs construct explicit problem models before generating solutions. Reduces constraint violations vs CoT and ReAct across five planning domains.
Understanding World or Predicting Future? A Comprehensive Survey of World Models
Two-function taxonomy separating world models that build internal representations (understanding) from those that predict future states (simulation/decision guidance); ACM CSUR extended version
V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning
Action-free JEPA pre-trained on 1M+ hours of video; V-JEPA 2-AC post-training on <62h robot video enables zero-shot pick-and-place on Franka arms
A Comprehensive Survey on World Models for Embodied AI
Three-axis taxonomy (Functionality × Temporal × Spatial) for embodied AI world models
A Survey of World Models for Autonomous Driving
Three-tiered taxonomy: future-world generation, behavior planning, integrated closed-loop systems
A Step Toward World Models: A Survey on Robotic Manipulation
Surveys manipulation methods exhibiting world-model capabilities — bridges VLA models and explicit world models
3D and 4D World Modeling: A Survey
Hierarchical taxonomy (VideoGen / OccGen / LiDARGen) for 3D/4D world models
LeWorldModel: Stable End-to-End Joint-Embedding Predictive Architecture from Pixels
First JEPA training stably end-to-end from raw pixels using only two loss terms — removes EMA/distillation tricks earlier JEPAs required
Causal-JEPA: Learning World Models through Object-Level Latent Interventions
Extends masked JEPA with object-centric representations; object-level masking induces counterfactual-like latent interventions
H-WM: Robotic Task and Motion Planning Guided by Hierarchical World Model
Hierarchical world model jointly predicting logical and visual state transitions — mitigates error accumulation in TAMP
Beyond Dense Futures: World Models as Structured Planners for Robotic Manipulation (StructVLA)
Structured sparse frame prediction for planning — avoids dense pixel rollouts by predicting physically meaningful keyframes
GAIA-2: A Controllable Multi-View Generative World Model for Autonomous Driving
Latent diffusion world model for AV — controllable multi-view video generation from structured conditioning; production tool at Wayve
PhyWorldBench: A Comprehensive Evaluation of Physical Realism in Text-to-Video Models
12,600-video empirical benchmark — quantifies systematic physics failures in Sora and peer generative video models
VideoScience-Bench: Benchmarking Scientific Understanding and Reasoning for Video Generation
Sora-2 ~64% / Veo-3 ~58.7% on Phenomenon Congruency — quantifies how far frontier video models are from ground-truth physical realism
LLM Reasoning Is Latent, Not the Chain of Thought
Argues LLM reasoning should be studied as latent-state trajectory formation, not faithful surface CoT — implications for interpretability, alignment, and training-objective design
AlphaEvolve: A Gemini-powered coding agent for designing advanced algorithms
Gemini-powered evolutionary coding agent; 0.7% Google compute recovery; math breakthroughs
Anthropic Transformer Circuits Thread & Circuit Tracing
Running research thread: features, circuits, superposition, attribution graphs, circuit tracing tools
Transformer Circuits Thread (Broader Research Program)
Foundational research thread on mechanistic interpretability: mathematical framework, superposition, monosemanticity
Genie 3: A New Frontier for World Models
First real-time interactive generative world model — 11B-param autoregressive transformer producing 720p navigable worlds at 24fps with ~1 minute visual memory
A Path Towards Autonomous Machine Intelligence (Version 0.9.2)
Canonical position paper proposing JEPA, configurable predictive world models, hierarchical planning, intrinsic motivation, and SSL as the blueprint for Autonomous Machine Intelligence
Meta Muse Spark — Native Multimodal Foundation Model with Contemplating Mode
Meta announces Muse Spark — natively multimodal (text/image/voice in single transformer) with Contemplating mode that orchestrates parallel sub-agents for deeper reasoning without latency penalty
Gemini 3 — Google's Latest Multimodal + Agentic Foundation Model
Google releases Gemini 3 — claimed best-in-world multimodal understanding and most powerful agentic model. Improved tool-use, planning, and rich multimodal output over Gemini 2.5
Mechanistic Interpretability — 10 Breakthrough Technologies 2026
Named mech interp as 2026 breakthrough; Anthropic microscope + CoT monitoring advances
AI Safety, Alignment, and Interpretability in 2026
DPO replacing RLHF analysis, alignment mirages concept, 6 documented failure modes, alignment trilemma
The AI Research Landscape in 2026: From Agentic AI to Embodiment
Synthesis of 2026 AI landscape across 5 frontiers: agentic AI mainstream, native multimodality standard, embodied/VLA scaling, world models + continual learning, autonomous agents in production