Knowledge catalogue
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
arXiv:2604.07705v1 Announce Type: new Abstract: Aerial vision-and-language navigation (Aerial VLN) aims to enable unmanned aerial vehicles (UAVs) to interpret natural language instructions and autonom
arXiv:2604.03486v2 Announce Type: replace-cross Abstract: We present VisionClaw, an always-on wearable AI agent that integrates live egocentric perception with agentic task execution. Running on Meta
arXiv:2604.06277v1 Announce Type: new Abstract: Existing hallucination detection methods for large language models (LLMs) rely on external verification at inference time, requiring gold answers, retri
arXiv:2604.08510v1 Announce Type: new Abstract: Large language models (LLMs) can perform remarkably complex tasks, yet the fine-grained details of how these capabilities emerge during pretraining rema
arXiv:2604.08513v1 Announce Type: new Abstract: Transfer learning followed by fine-tuning is widely adopted in medical image classification due to consistent gains in diagnostic performance. However,
arXiv:2604.06422v1 Announce Type: cross Abstract: Understanding when Vision-Language Models (VLMs) will behave unexpectedly, whether models can reliably predict their own behavior, and if models adher
arXiv:2604.08281v1 Announce Type: new Abstract: Large reasoning models (LRMs) have achieved strong performance enhancement through scaling test time computation, but due to the inherent limitations of
arXiv:2604.08032v1 Announce Type: cross Abstract: Automated maritime collision avoidance will rely on human supervision for the foreseeable future. This necessitates transparency into how the system p
arXiv:2603.28906v2 Announce Type: replace Abstract: AGI has become the Holly Grail of AI with the promise of level intelligence and the major Tech companies around the world are investing unprecedente
arXiv:2604.06901v1 Announce Type: cross Abstract: Conventional career guidance platforms rely on static, text-driven interfaces that struggle to engage users or deliver personalised, evidence-based in
a useful mental model on how teams can think about good data design to improve their models/agents: Evals ~= Training Data ~= Environments - in Classical Deep Learning, we learn from each training exa
FlowInOne is a vision-centric multimodal image generation framework that reformulates multimodal generation as a purely visual flow, converting all inputs into visual prompts and enabling a clean i...
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...
DeCarlos Brown Jr., a man diagnosed with schizophrenia who had been previously arrested 14 times on charges ranging from illegal firearm possession to felony robbery and assault, stabbed Ukrainian ...
This 10-min read from @Vtrivedy10 changes how you build AI agents. Most people are stuck in the same loop; switching models when agents break. The reframe: evals are the training data for your harness
Cursor's code review agent, **Bugbot**, now supports real-time self-improvement by learning from activity on pull requests. Bugbot reviews hundreds of thousands of PRs per day and uses signals fro...
In this post, we'll walk you through a complete implementation of model fine-tuning in Amazon Bedrock using Amazon Nova models, demonstrating each step through an intent classifier example that achiev
The search results did not return the specific Reddit post content. Based on what was retrieved, I'm unable to produce a fully sourced factual summary of that particular Reddit thread about the LQS...
Google Research introduced two AI agents to streamline academic workflows: **PaperVizAgent**, a visualizer agent for drawing academic figures, and **ScholarPeer**, a reviewer agent that automatica...
Physical Intelligence (Pi) is building a general-purpose robotic intelligence system whose core Visual-Language-Action (VLA) model takes visual observations, natural-language instructions, and the...
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
GLM-5.1 is Zhipu AI's next-generation flagship model for agentic engineering, achieving state-of-the-art performance on SWE-Bench Pro and leading its predecessor GLM-5 by a wide margin on NL2Repo (...
Visually rich documents are especially challenging for agents. Tables, charts, and images often break traditional document pipelines, making complex reasoning difficult📄 So we teamed up with @lancedb
PwC rolled out Copilot to employees globally. PwC reported $150 million in time savings from Copilot use in a Microsoft customer story.
Anthropic reports Zapier uses Claude in marketing, engineering, research and design; its AI-wide adoption figures are not Claude-only.