Nous Research Releases Contrastive Neuron Attribution (CNA): Sparse MLP Circuit Steering Without SAE Training or Weight Modification
Nous Research releases Contrastive Neuron Attribution (CNA), a method that identifies and ablates sparse MLP neuron circuits to steer LLM behavior — no sparse autoencoder training, no weight modification, and no degradation of general capability benchmarks.
The post Nous Research Releases Contrastiv...
Perplexity Open-Sources Bumblebee: A Read-Only Supply-Chain Scanner for Developer Endpoints
Perplexity has open-sourced Bumblebee, an internal security tool it uses to protect the developer systems behind its search product, Comet, and Computer. Bumblebee is a read-only inventory collector for macOS and Linux developer endpoints. It scans npm, PyPI, Go modules, MCP configs, editor extensio...
Benchmarking and Improving Monitors for Out-Of-Distribution Alignment Failure in LLMs
arXiv:2605.21602v1 Announce Type: new
Abstract: Many safety and alignment failures of large language models (LLMs) occur due to out-of-distribution (OOD) situations: unusual prompt or response patterns that are unforeseen by model developers. We systematically study whether LLM monitoring pipelines...
The Shape of Testimony: A Scalable Framework for Oral History Archive Comparison
arXiv:2605.21623v1 Announce Type: new
Abstract: Researchers in Holocaust studies have often distinguished between two styles of oral survivor testimony: the USC Shoah Foundation's interviews tend to follow a structured, interviewer-guided format, whereas the Yale Fortunoff Video Archive generally f...
MindLoom: Composing Thought Modes for Frontier-Level Reasoning Data Synthesis
arXiv:2605.21630v1 Announce Type: new
Abstract: Although LLMs have made substantial progress in reasoning, systematically producing frontier-level reasoning data remains difficult. Existing synthesis methods often have limited visibility into the structural factors that govern problem difficulty, w...
AOP-Wiki EMOD 3.0: Data Model Expansions and Content Evaluation Framework for Using Agentic AI to Improve Integration between AOPs and New Approach Methodologies (NAMs)
arXiv:2605.21645v1 Announce Type: new
Abstract: Adverse Outcome Pathways (AOP) are logic models that causally link biological mechanisms that can be measured in a lab to adverse outcomes, relevant to chemical regulatory endpoints. AOPs contextualize new approach methodologies (NAMs), in vitro and i...
Hybrid AI: Combining Deterministic Analytics with LLM Reasoning
How AI architecture prevents plausible but wrong analytics
The post Hybrid AI: Combining Deterministic Analytics with LLM Reasoning appeared first on Towards Data Science.
Qwen3.7-Max: Alibaba’s New Agent-First LLM for Coding, Reasoning, and Long-Horizon AI Workflows
Alibaba’s Qwen team has unveiled Qwen3.7-Max, a flagship model built for the agent era. Unlike conventional chatbot-focused LLMs, it is designed as a foundation for autonomous AI agents that can code, debug, use tools, manage workflows, and execute long-running enterprise tasks. Alibaba claims the m...
We kicked off our new weekly series This Week in AI on Monday, and we covered a lot of ground in 30 minutes, including an AI model that found security holes faster than decades of human auditing, a data center in Utah the size of two Manhattans, and a practical argument for why the harness […]
Enterprise Document Intelligence: A Series on Building RAG Brick by Brick, from Minimal to Corpus scale
For AI engineers who want to understand every step, not just call the library
The post Enterprise Document Intelligence: A Series on Building RAG Brick by Brick, from Minimal to Corpus scale appeared first on Towards Data Science.
SpaceX files to go public, and the math requires a little faith
The SpaceX S-1 is finally here, and the story it tells goes way further than rockets. The filing runs to 36 pages of risk factors alone, and the numbers inside match the ambition: a $28 trillion total addressable market, a pay package tied to establishing a Mars colony, and a valuation target that w...
The Hidden Bottleneck in Quantum Machine Learning: Getting Data into a Quantum Computer
Quantum Machine Learning promises access to exponentially large representational spaces, but before any computation can happen, classical data must first be embedded into quantum systems. This article explores one of the most overlooked bottlenecks in QML: getting data into a quantum computer effici...
Google I/O showed how the path for AI-driven science is shifting
During Tuesday’s Google I/O keynote, Demis Hassabis, the CEO of Google DeepMind, proclaimed that we are currently “standing in the foothills of the singularity.” It was a striking statement—the singularity is the theoretical future moment when AI rapidly exceeds human intelligence and dramatically t...
Microsoft Releases Fara1.5: A Family of Browser Computer-Use Agents (4B/9B/27B) That Outperform OpenAI Operator and Gemini 2.5 Computer Use on Online-Mind2Web
Microsoft Research released Fara1.5, a family of browser computer-use agents in 4B, 9B, and 27B sizes. Fara1.5-27B scores 72% on Online-Mind2Web, outperforming OpenAI Operator, Gemini 2.5 Computer Use, and Yutori Navigator n1. The release also includes FaraGen1.5, a synthetic data pipeline that trai...
Build Recurrent-Depth Transformers with OpenMythos for MLA, GQA, Sparse MoE, and Loop-Scaled Reasoning
In this tutorial, we explore OpenMythos by building an advanced recurrent-depth transformer workflow that runs end-to-end in Google Colab. We create both MLA and GQA model variants, compare their parameter counts, and check the stability of the recurrent injection matrix through its spectral radius....
Temporal Contrastive Transformer for Financial Crime Detection: Self-Supervised Sequence Embeddings via Predictive Contrastive Coding
arXiv:2605.21490v1 Announce Type: new
Abstract: We introduce the Temporal Contrastive Transformer (TCT), a representation learning framework designed to capture contextual temporal dynamics in sequences of financial transactions. The model is trained using a self-supervised contrastive objective to...
Teaching Language Models to Forecast Research Success Through Comparative Idea Evaluation
arXiv:2605.21491v1 Announce Type: new
Abstract: As language models accelerate scientific research by automating hypothesis generation and implementation, a new bottleneck emerges: evaluating and filtering hundreds of AI-generated ideas without exhaustive experimentation. We ask whether LMs can lear...
The Attribution Impossibility: No Feature Ranking Is Faithful, Stable, and Complete Under Collinearity
arXiv:2605.21492v1 Announce Type: new
Abstract: No feature ranking can be simultaneously faithful, stable, and complete when features are collinear. For collinear pairs, ranking reduces to a coin flip. We prove this impossibility, quantify it for four model classes, resolve it via ensemble averagin...
OpenAI named a Leader in enterprise coding agents by Gartner
OpenAI is named a leader in the 2026 Gartner Magic Quadrant for Enterprise AI Coding Agents, with Codex recognized for innovation and enterprise-scale deployment.
How CopilotKit Is Redefining the Agentic AI Stack in 2026
An inside look at CopilotKit’s 2026 shipping cycle. Learn how the new AG-UI protocol, AIMock testing suite, and Pathfinder server are providing the production architecture developers need for agentic AI.
The post How CopilotKit Is Redefining the Agentic AI Stack in 2026 appeared first on MarkTechPos...