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arXiv:2604.07316v1 Announce Type: new Abstract: The growing complexity of neural networks hinders the deployment of distributed machine learning on resource-constrained devices. Split learning (SL) of

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Model Releases

SpecQuant: Spectral Decomposition and Adaptive Truncation for Ultra-Low-Bit LLMs Quantization

DGX agent

arXiv:2511.11663v2 Announce Type: replace-cross Abstract: The emergence of accurate open large language models (LLMs) has sparked a push for advanced quantization techniques to enable efficient deploy

model-releasesarxiv-cs-ai

10 Apr 2026

Towards provable probabilistic safety for scalable embodied AI systems

arXiv:2506.05171v3 Announce Type: replace-cross Abstract: Embodied AI systems, comprising AI models and physical plants, are increasingly prevalent across various applications. Due to the rarity of sy

Variational Feature Compression for Model-Specific Representations

arXiv:2604.06644v1 Announce Type: cross Abstract: As deep learning inference is increasingly deployed in shared and cloud-based settings, a growing concern is input repurposing, in which data submitte

ViVa: A Video-Generative Value Model for Robot Reinforcement Learning

arXiv:2604.08168v1 Announce Type: new Abstract: Vision-language-action (VLA) models have advanced robot manipulation through large-scale pretraining, but real-world deployment remains challenging due

Tools

Zero-configuration Django support

Vercel now supports Django with zero configuration, enabling developers to instantly deploy Django full-stack applications or APIs without any manual setup. Vercel automatically detects Django's `m...

toolsvercel-blog

Tools

Zero-configuration Go backend support

Vercel now supports Go backend applications with zero configuration, allowing developers to deploy Go APIs and Go Gin API applications without any configuration required. Go files placed inside ...

toolsvercel-blog

92% of COBOL developers are expected to retire in the next four years, and 68% of enterprise COBOL modernizations are failing. Agents can he…

applicationscognition-ai--x

92% of COBOL developers are expected to retire in the next four years, and 68% of enterprise COBOL modernizations are failing. Agents can help – we wrote up how: https://cognition.ai/blog/how-devin-is

Blaize launches AI Services platform to move enterprise AI from pilot to production

model-releasessiliconangle

Artificial intelligence computing company Blaize Holdings Inc. today announced the launch of Blaize AI Services, a new platform designed to help AI infrastructure providers and enterprises deploy prod

Deep Agents or @LangChain? Just use the right tool for the right job

model-releasesharrison-chase--x

Deep Agents or @LangChain? Just use the right tool for the right job great q! deepagents has more 'batteries included', which langchain v1 is a very minimalistic agent harness if you are doing more co

great q! deepagents has more 'batteries included', which langchain v1 is a very minimalistic agent harness if you are doing more complex wor…

model-releasesharrison-chase--x

great q! deepagents has more 'batteries included', which langchain v1 is a very minimalistic agent harness if you are doing more complex workflows (eg claude code for X) -> deepagents if you want some

Previewing Interrupt 2026: Agents at Enterprise Scale

applicationslangchain-blog

Interrupt 2026 is LangChain's second annual AI agent conference, scheduled for May 13–14 at The Midway in San Francisco, focused on the question of how to deploy and operate AI agents at enterprise...

Thrilled to announce the Monitor tool which lets Claude create background scripts that wake the agent up when needed. Big token saver and gr…

model-releasesboris-cherny--x

Thrilled to announce the Monitor tool which lets Claude create background scripts that wake the agent up when needed. Big token saver and great way to move away from polling in the agent loop Claude c

The new Anthropic managed agents API is basically the Letta API that we've had since a year ago, but closed source and with provider lock-in…

model-releasesharrison-chase--x

The new Anthropic managed agents API is basically the Letta API that we've had since a year ago, but closed source and with provider lock-in. They even have read-only memory blocks and memory block sh

8 Apr 2026

The next phase of enterprise AI

Enterprise revenue now accounts for more than 40% of OpenAI's total revenue and is on track to reach parity with consumer revenue by the end of 2026. The company is observing a key shift in how l...

applicationsopenai

8 Apr 2026

Anthropic's Project Glasswing - restricting Claude Mythos to security researchers - sounds necessary to me

model-releasessimon-willison

Anthropic didn't release their latest model, Claude Mythos (system card PDF), today. They have instead made it available to a very restricted set of preview partners under their newly announced Projec

7 Apr 2026

🔓 Open-source release Get DeepSeek-V4.1-Flash-1017: 🤗 Hugging Face: https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash-1017 🔗 ModelSc…

model-releasesdeepseek--x

🔓 Open-source release Get DeepSeek-V4.1-Flash-1017: 🤗 Hugging Face: https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash-1017 🔗 ModelScope: https://modelscope.cn/models/deepseek-ai/DeepSeek-V4.1-Fla

17 Oct 2026

A Quantum Machine Learning Approach to Content-Based Media Recommendation

arXiv:2610.21562v1 Announce Type: new Abstract: We use quantum machine learning techniques to develop a content-based media recommender system and evaluate its performance on TV programmes using textu

Agents

Agentic-Priors: Using Large Language Models to Address the Cold Start Problem in Preference Elicitation

arXiv:2610.21938v1 Announce Type: cross Abstract: An agent that learns a user's preferences from their choices faces a cold start problem: before any choices are observed, it must rely solely on a pri

agentsarxiv-cs-ai

Benchmarking Code LLM-as-a-Judge via Constrained Perturbation and Calibration

arXiv:2512.20159v2 Announce Type: replace-cross Abstract: Code from LLM-assisted development may contain defects like API hallucinations, motivating the development of code evaluation metrics to asses

Evolving Together, Failing Apart: The Skill-Policy Co-evolution Trap in Self-Improving Agents

arXiv:2610.20845v1 Announce Type: new Abstract: Skill-policy co-evolution, in which an agent's policy model and its skill bank improve each other during training, is a promising paradigm for self-impr

IDfRA: Self-Verification for Iterative Design in Robotic Assembly

arXiv:2509.16998v2 Announce Type: replace Abstract: Design for Robotic Assembly (DfRA) remains largely dependent on manual planning and heuristic simulation, limiting scalability and robustness in com

applicationsarxiv-cs-ro

Jev-as-a-Judge for RAG Claim Verification: Confidence-Gated Cascading Between a Non-Generative Verifier and a Frontier LLM

model-releasesarxiv-cs-cl

arXiv:2610.20634v1 Announce Type: new Abstract: Retrieval-augmented generation asks one question at volume: does this evidence support this claim? The answer is one bit, yet most pipelines obtain it f

Hardware

Making every stage of medical device document assessment with large language models deterministic

arXiv:2610.21300v1 Announce Type: new Abstract: To show that a medical device complies with regulation, experts judge whether documents and records meet each requirement and record the judgment for ot

hardwarearxiv-cs-cl

Multi-Teacher On-Policy Distillation for Flow-Based Vision-Language-Action Models

arXiv:2610.21522v1 Announce Type: new Abstract: Specialized vision-language-action (VLA) policies acquire strong domain-specific skills, yet consolidating these skills into one shared policy remains c

O-RAN-Native Jamming Detection Under Network Heterogeneity

arXiv:2610.20816v1 Announce Type: new Abstract: Radio-frequency jamming threatens cellular network operations in contested environments. The Open Radio Access Network (O-RAN) architecture exposes per-

PROBE: Learning to Audit Policy Compliance in Tool-Using LLM Agents

arXiv:2610.22124v1 Announce Type: new Abstract: Modern agentic systems extend language models with external tools, enabling them to complete complex tasks through multi-turn interactions. As these age

RAG-RST: Retrieved Exemplars as In-Context Discourse Schema for RST Parsing

arXiv:2610.22150v1 Announce Type: new Abstract: In Rhetorical Structure Theory (RST), each edge of a discourse tree carries a nuclearity label, marking which span holds the central content, and a rela

Spark-0: Scaling Spatially Aligned Tactile Pretraining for Robot Dexterous Manipulation

model-releasesarxiv-cs-ro

arXiv:2610.22342v1 Announce Type: new Abstract: Generalist robot policies benefit from large-scale visual pretraining but often struggle with contact-rich dexterous manipulation, where force, complian

Towards bio-inspired visual navigation: a neuromorphic navigation paradigm for MAVs

arXiv:2610.21978v1 Announce Type: new Abstract: Biological visual navigation achieves remarkable robustness at extremely low power, whereas frame-based robotic systems relying on artificial neural net

X-RIC: An Agentic RAN-Intelligent Controller Benchmark for Enhancing Reinforcement Learning

arXiv:2610.22269v1 Announce Type: new Abstract: The O-RAN ALLIANCE introduces architectural flexibility through disaggregation and AI-driven control. While the RAN Intelligent Controller (RIC) enables

Agents

A Global View of How LLMs Value Human Time

arXiv:2610.18515v2 Announce Type: cross Abstract: Large language models (LLMs) increasingly act as personal assistants; however, little is known about how they capture national-level preferences on a

agentsarxiv-cs-ai

A Graph-Based Analysis of Comparability, Scale, and Attribution in Private Transformer Inference

arXiv:2610.19607v1 Announce Type: cross Abstract: Rising privacy concerns around large language models have accelerated research in private Transformer inference (PTI). Synthesizing the empirical clai

applicationsarxiv-cs-lg

AgentStripes: An Evidence-Graded Maturity Model for AI Agents

arXiv:2610.18603v1 Announce Type: new Abstract: Benchmarks report what an Artificial Intelligence (AI) agent can do on a task suite, but not whether one released version has been engineered with the c

Bridging Academia and Industry: A Comprehensive Benchmark for Attributed Graph Clustering

arXiv:2602.08519v2 Announce Type: replace Abstract: Attributed Graph Clustering (AGC) is a fundamental unsupervised task that integrates structural topology and node attributes to uncover latent patte

Can Agents Truly Forget? Explore Machine Unlearning for LLM Agents

arXiv:2610.17659v1 Announce Type: new Abstract: Large language model (LLM) agents have shown strong capabilities in interactive problem solving, tool use, and long-horizon task execution. However, the

Research

Comparative Evaluation of Deep-Learning based DoA Estimators for Real-Time ISAC Beamforming

arXiv:2610.20326v1 Announce Type: new Abstract: Integrated Sensing and Communication (ISAC) systems rely on accurate Direction-of-Arrival (DoA) estimation for effective beamforming and spectral-effici

researcharxiv-cs-lg

Counterfactual Regret for Reflective Agents with Lean-Verified Guarantees

arXiv:2610.14790v1 Announce Type: new Abstract: Reflective language agents reuse feedback and memory to adapt across tasks without updating model weights. However, existing guarantees for policy selec

DarKnight: Retrieval-Guided Agentic Framework for Breaking Dark Web CAPTCHA Gates

model-releasesarxiv-cs-cv

arXiv:2610.19830v1 Announce Type: cross Abstract: Cyber Threat Intelligence (CTI) investigators who monitor dark web marketplaces for leaked credentials and breach listings must pass the diverse CAPTC

E2DRL: End-to-End Differentiable Reinforcement Learning for 3D Obstacle Avoidance in Quadruped Robots

arXiv:2610.19627v1 Announce Type: new Abstract: Differentiable reinforcement learning shows strong promise for robot policy learning, but its application to legged locomotion has remained limited to b

Agents

EvoQuantLab: Training-Free Dual-Loop Evolution for Auditable Quantitative Research

arXiv:2610.17130v2 Announce Type: new Abstract: Automated alpha factor discovery is critical for modern quantitative research. While large language models (LLMs) have increasingly been integrated into

agentsarxiv-cs-ai

Few-Shot Adaptation for Anomalous Sound Detection at Low False-Positive Rate

arXiv:2610.19893v1 Announce Type: cross Abstract: Reliable fault detection is crucial for industrial machinery in large-scale facilities, where unexpected failures can cause costly downtime and produc

applicationsarxiv-cs-lg

FleetPilot: Fine-Grained Steering Empowers Real-World LLM Personalization

arXiv:2610.14970v1 Announce Type: new Abstract: With the rapid evolution of large language models (LLMs), there is an increasing demand for effective personalization techniques that can adapt model be

applicationsarxiv-cs-ai

Following the Flow the Law Requires: Training Voice Agents to Transfer to Unseen Regulated Procedures in Debt Collection

model-releasesarxiv-cs-cl

arXiv:2610.18881v1 Announce Type: new Abstract: Voice agents built on large language models (LLMs) now handle customer calls, but in regulated applications completing the task is not enough: the agent

Research

From Efficiency to Sufficiency: The Cost-Aware Measurement Design Framework for Automated Essay Scoring

arXiv:2610.19287v1 Announce Type: cross Abstract: Compute cost in automated essay scoring (AES) is usually treated as a technical efficiency issue rather than a measurement design concern. Yet deploym

researcharxiv-cs-cl

Frustratingly Easy Agentic RAG via Portable Skills: A Case Study in Customer Support

arXiv:2610.14428v1 Announce Type: new Abstract: Enterprise workflow automation typically requires retrieving a complete and accurate set of relevant information from large operational document corpora

How Visko streams real-time world models on Google Cloud TPUs

model-releasesgoogle-cloud-ai

Editor's note: Generative AI startups are moving rapidly beyond static clip generation to build interactive, real-time worlds. In this technical deep dive, we explore how AI startup Visko collaborated

Measuring the Inference Energy Efficiency of Open-Weight LLMs across Benchmarks, Reasoning Modes, and Hardware

arXiv:2610.14389v1 Announce Type: new Abstract: Benchmark scores tell us what an LLM can do, but not how much energy is required to deliver that capability. We directly measure this trade-off for 86 o