Search: “deployment”

Sigma Automate emerges with $2.75M to tackle enterprise IT complexity with no-code automation

Sigma Automate Inc., a startup providing enterprises with no-code information technology automation, formally launched today with $2.75 million in funding to scale up its platform and expand its abili

applicationssiliconangle

9 Apr 2026

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Model Releases

You want a strong opensource and fully customisable harness?! None other than langchain’s deepagents. Try it yourself if in doubt.

DGX agent

You want a strong opensource and fully customisable harness?! None other than langchain’s deepagents. Try it yourself if in doubt. most of the agents we see being built do this the main cases where we

model-releasesharrison-chase--x

9 Apr 2026

'Claude Code isn't magic. The harness layer is just software, and software is something any dev can shape to fit how they want to work.' Che…

model-releasesharrison-chase--x

'Claude Code isn't magic. The harness layer is just software, and software is something any dev can shape to fit how they want to work.' Check out @Hacubu’s practical guide to building a custom agent

Google Cloud named a Leader in The Forrester Wave™: Sovereign Cloud Platforms, Q2 2026

applicationsgoogle-cloud-ai

In today’s global economy, data is a strategic asset. For many organizations — particularly those in highly regulated industries and the public sector — the ability to innovate with AI is often balanc

Tutorials

Hands on, concrete guide (with code!) for harness hill climbing with evals

tutorialsharrison-chase--x

LangChain's 'Better Harness' tutorial, authored by Product Manager Vivek Trivedy and shared by Harrison Chase (@hwchase17), presents a hands-on, code-driven guide for using evaluations (evals) as a...

Highlights: 👉 28% coding improvement over GLM-5 with refined RL post-training 👉 Better long-horizon execution across hundreds of rounds an…

Highlights: 👉 28% coding improvement over GLM-5 with refined RL post-training 👉 Better long-horizon execution across hundreds of rounds and thousands of tool calls 👉 Thinking mode, tool calling, and s

agentstogether-ai--x

If you're an AI/agent builder, it's so important that you don't overbuild and overcommit on a specific toolset and infrastructure. Frontier …

model-releasesjerry-liu--x

If you're an AI/agent builder, it's so important that you don't overbuild and overcommit on a specific toolset and infrastructure. Frontier labs are shipping not just the models, but the harnesses and

Companies

OpenAI

Human

AI research and deployment company behind ChatGPT, the GPT model family, Codex, and the OpenAI API — heavily represented in this wiki’s model-releases and safety corpus.

openaichatgptgpt

11 Dec 2015

we are rolling out the updated model to users who are using deepseek-v4.1-flash as well.

On October 17, 2026, Ollama (via its Twitter account @ollama) announced that it was rolling out an updated model to customers currently using the DeepSeek‑v4.1‑Flash language model. The update is avai

model-releasesollama--x

17 Oct 2026

Are You Sure Your LLM Is Sure? Repairing and Auditing Confidence

arXiv:2610.22139v1 Announce Type: new Abstract: Confidence scores determine whether an LLM answer is accepted, reviewed, or regenerated, yet scalar recalibration can only correct errors visible throug

ARGUS: An Agenda-Driven Framework for Reliable User Simulation

arXiv:2610.21346v1 Announce Type: new Abstract: High-fidelity user simulators are essential for evaluating and training agents in interactive environments. However, current LLM-based simulators strugg

AVALON: Zero-Shot Indoor Navigation with Human-Seeded Topological Memory

arXiv:2610.21586v1 Announce Type: cross Abstract: Indoor service robots often enter unmapped buildings whose layouts and task constraints are already familiar to users. We address this human-familiar,

safetyarxiv-cs-ai

CARE-SD: Explainable Reasoning Architecture for Local SLM Self-Disclosure Analysis in Textual Data

arXiv:2610.21151v1 Announce Type: cross Abstract: Cybersecurity interviews uncover critical security experiences, behaviors, and privacy concerns often not fully captured by conventional technical ass

CarryOn: A Dual-Loop Harness for Personalized and Reliable Robot Assistance

arXiv:2610.21453v1 Announce Type: cross Abstract: While generalist vision-language-action (VLA) models have enabled diverse open-world manipulation, real-world robotic assistance requires two critical

safetyarxiv-cs-cv

Causal Analysis of Robot Foundation Models Enables Efficiency Gains

arXiv:2610.20750v1 Announce Type: new Abstract: Vision-language-action (VLA) models are a promising approach to general purpose robot manipulation. While the internal computation of vision-language mo

researcharxiv-cs-ro

China proposes export controls on 23 AI technologies (including large models, agents & clusters); already open-sourced tech is exempted

model-releasesr-localllama

On October 16, 2026, China’s Ministry of Commerce and Ministry of Science and Technology released a draft revision to the Catalog of Technologies Prohibited and Restricted from Export. It proposes add

Compliant GMT: Making General Motion Tracking Compliant via Residual Reference Adaptation

arXiv:2610.22119v1 Announce Type: new Abstract: We propose Compliant GMT (C-GMT), a modular framework for full-body compliant responses in general motion tracking. As humanoid robots move into real wo

safetyarxiv-cs-ro

DeepUnfolding_Agent: A Classical_Quantum Adaptive Control API

arXiv:2610.20615v1 Announce Type: new Abstract: Adaptive optimization workflows in machine learning, federated learning, quantum machine learning, and hybrid classical quantum systems often embed cont

DefoliationCAM: An Edge-AI System for Real-Time Insect Defoliation Severity Assessment in Grapevines

arXiv:2610.20879v1 Announce Type: new Abstract: Insect-induced defoliation threatens grapevine health and yield, yet severity assessment relies on subjective manual scouting. We developed DefoliationC

local-aiarxiv-cs-cv

Dexterity from Supervised Play

arXiv:2610.22340v1 Announce Type: cross Abstract: How can robots autonomously collect the contact-rich experience needed to learn dexterous manipulation? We present DSP: Dexterity from supervised play

safetyarxiv-cs-ai

Does Personalization Break Trust? Open-Set Rejection Calibration Under Few-Shot On-Device Intent Adaptation

arXiv:2610.20652v1 Announce Type: new Abstract: Always-on virtual assistants increasingly personalize on-device to new user-specific commands via few-shot fine-tuning (e.g., LoRA), but this adaptation

local-aiarxiv-cs-cl

Failure Is the Mother of Success: Recovering Supervision with Grounding Hindsight

arXiv:2610.21018v1 Announce Type: new Abstract: When every rollout for a problem fails, GRPO receives neither a successful exemplar nor a nonzero group-relative advantage, so it learns nothing from ex

safetyarxiv-cs-ai

FALCON: FPGA-Accelerated Latency-Certifiable Occupancy Networks for Camera-Based Autonomous Driving

model-releasesarxiv-cs-cv

arXiv:2610.22143v1 Announce Type: new Abstract: A perception system that must brake for a pedestrian does not need a low average latency. It must deliver an answer before the deadline on every frame,

Fault Detection and Bit-Error Rate Diagnostics in Optical Wireless Links Using Edge-AI

arXiv:2610.21402v1 Announce Type: new Abstract: Optical Wireless Communication (OWC) systems provide high-bandwidth, spatially secure, and RF-interference-free digital transmission. However, direct fr

local-aiarxiv-cs-lg

FDE-Gym: The Last Mile of AI Delivery

arXiv:2610.22350v1 Announce Type: new Abstract: Existing agent benchmarks typically evaluate agents on well-specified tasks defined by issue reports, specifications, or task tickets. Real-world custom

FedSkillGit: Federated Skill Evolution via Version Control

arXiv:2610.21348v1 Announce Type: new Abstract: Large language model agents can improve their capabilities by evolving reusable natural-language skills from execution experience. In real-world deploym

local-aiarxiv-cs-ai

FedSumUp: User-Auditable Privacy-Aware Representation Sharing for Resource-Constrained Federated Intelligence

arXiv:2610.21194v1 Announce Type: cross Abstract: Existing federated data condensation methods face privacy risks, as uploaded synthetic data may preserve sensitive information and remain vulnerable t

FilterFusion: Prior-Guided Adaptive Filter Fusion for Efficient Video Denoising

arXiv:2610.21505v1 Announce Type: new Abstract: Real-world video denoising for communication systems must handle mixed degradations such as sensor noise, compression artifacts, and motion-induced inco

applicationsarxiv-cs-cv

Hy-Memory-30B-A3B: Attributed Reinforcement Learning for Long-Term Memory Writing

arXiv:2610.22196v1 Announce Type: new Abstract: External-memory systems extend language-model applications beyond a context window, but their quality depends critically on the model executing the writ

Improving Environment-Agnostic Coding Agents: The Role of Scaffolding

arXiv:2610.22289v1 Announce Type: new Abstract: Stronger language models may increasingly construct useful procedures for themselves, reducing the advantage of developer-supplied scaffolding. We inves

KODA: Kinematics--Observation Data Alignment for Humanoid Learning from Human Egocentric Demonstration

arXiv:2610.21152v1 Announce Type: new Abstract: Training humanoid whole-body vision-language-action (VLA) policies requires costly robot demonstrations with aligned robot-view observations and control

safetyarxiv-cs-ro

Large Language Models Naively Recover Ethnicity from Individual Records

arXiv:2601.21132v2 Announce Type: replace Abstract: I demonstrate that large language models can infer ethnicity from names with accuracy exceeding that of Bayesian Improved Surname Geocoding (BISG) w

Learning When to Think: Utility-Guided Adaptive Reasoning for Efficient Text Retrieval

arXiv:2610.21030v1 Announce Type: cross Abstract: Reasoning-conditioned embeddings can improve retrieval by progressively refining semantic constraints. However, additional reasoning may introduce ove

LLMR: Knowledge Distillation with a Large Language Model-Induced Reward

arXiv:2409.12500v2 Announce Type: replace-cross Abstract: Large language models have become increasingly popular and demonstrated remarkable performance in various natural language processing (NLP) ta

Market Incentives for AI Safety Investment

arXiv:2610.21607v1 Announce Type: new Abstract: Despite their practical significance, modern AI systems pose significant societal risks, including toxicity, malicious use, and misinformation. Their mi

safetyarxiv-cs-lg

MARS: A Momentum-Aware Adaptive Rating System for Personalized Assessment

arXiv:2610.21685v1 Announce Type: cross Abstract: Adaptive assessment systems personalize learning by estimating learner proficiency and recommending suitable questions. However, many existing approac

safetyarxiv-cs-lg

MetaExp: Learning to Self-Improve through Experience via Verifiable Cross-Task Environment Scaling

arXiv:2610.21492v1 Announce Type: new Abstract: Language-model agents can accumulate interaction feedback, but reliably turning that feedback into reusable experience remains challenging. Existing met

Money-Mule Detection as a Relational Learning Problem: A Study on the RBIH NFPC Dataset

arXiv:2610.21314v1 Announce Type: new Abstract: Money-mule networks move criminal funds through many small transfers, each of which looks ordinary on its own. What marks an account as a mule lies outs

applicationsarxiv-cs-ai

MOSS: Mode-Oriented Source Shaping for Robot Flow Matching Policies

arXiv:2610.22193v1 Announce Type: new Abstract: In robotic manipulation, the same observation often admits multiple feasible actions. Generative policies such as diffusion and flow matching naturally

local-aiarxiv-cs-ro

Plans Are Not Executions: Adapting Frozen World-Model Planners to Controller-Induced Execution Shift

arXiv:2610.22041v1 Announce Type: new Abstract: World-model planners evaluate candidate trajectories by predicting their future consequences, implicitly relying on the plan-to-motion relationship lear

researcharxiv-cs-ro

PRISM: PRIvileged Sibling-guided Multi-Agent Topology Design

arXiv:2610.20628v1 Announce Type: new Abstract: Multi-agent systems (MAS) based on large language models (LLMs) have become a powerful way to address complex problems, and their effectiveness depends

agentsarxiv-cs-cl

QuasiLeak-Bench: Evaluating LLM-Based Privacy Detectors on Policy-Conditioned Quasi-Evidence Group Recovery

arXiv:2610.21333v1 Announce Type: new Abstract: Natural language messages often contain quasi-identifiers that are weak in isolation but can jointly reveal an individual's private attributes. We call

RAC: A Relational Agent Contract for Constraint-Governed Engineering Tasks

arXiv:2610.20935v1 Announce Type: new Abstract: Engineering agents must produce artifacts that satisfy exact, coupled constraints. Existing solutions often require agents to make semantic decisions an

agentsarxiv-cs-ai

Race to Recovery: Designing Advanced Safety Systems for Autonomous Driving via Learning Autonomous Racing

arXiv:2610.20873v1 Announce Type: new Abstract: Vehicles that lose control at the handling limit through icing, hydroplaning, or an abrupt evasive maneuver fall outside the operating envelope of produ

safetyarxiv-cs-ro

Ranked Right, Sized Wrong: Ensemble Spread Fails Silently at Streamflow Extremes

arXiv:2610.20947v1 Announce Type: cross Abstract: Deep learning models, particularly Long Short-Term Memory networks, are increasingly used for operational streamflow forecasting, with ensemble spread

safetyarxiv-cs-lg

Reinforcement Learning-driven Diffusion Models: Language, Vision, and Beyond

arXiv:2610.21539v1 Announce Type: new Abstract: Diffusion models (DMs) have steadily demonstrated outstanding performance in high-fidelity, controllable generation across diverse scenarios, following

agentsarxiv-cs-ai

REKI: Registering Knowledge in VLAs

arXiv:2610.22178v1 Announce Type: cross Abstract: We introduce REKI, a 2.4B vision-language-action model (VLA) pretrained exclusively on public data that sets a new Pareto frontier between performance

safetyarxiv-cs-cv

Retrieved but Not Read: Understanding Why Search-Augmented LLMs Fail to Use Available Evidence

arXiv:2610.21731v1 Announce Type: cross Abstract: Web search allows LLMs to access up-to-date information, but it remains unclear why they sometimes produce outdated answers even when relevant evidenc