Search: “concepts”

Group-Equivariant Poincare Convolutional Networks

arXiv:2607.00556v1 Announce Type: cross Abstract: While recent advancements like the Poincare ResNet have demonstrated the potential of learning visual representations directly in hyperbolic space, th

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Knowdit: Agentic Smart Contract Vulnerability Detection with Auditing Knowledge Summarization

DGX agent

arXiv:2603.26270v2 Announce Type: replace-cross Abstract: Smart contracts govern billions of dollars in decentralized finance (DeFi), yet automated vulnerability detection remains challenging because

agentsarxiv-cs-ai

2 Jul 2026

Planning over MAPF Agent Dependencies via Multi-Dependency PIBT

arXiv:2603.23405v2 Announce Type: replace-cross Abstract: Modern Multi-Agent Path Finding (MAPF) algorithms must plan for hundreds to thousands of agents in congested environments within a second, req

agentsarxiv-cs-ai

Retrieved Images as Visual Thought: Training-Free Multimodal In-Context Learning for the Open-vs-Closed Gap

model-releasesarxiv-cs-cv

arXiv:2607.00606v1 Announce Type: new Abstract: Recent work on Thinking with Images makes vision a dynamic part of reasoning, but does so through generation: the model invokes external tools, synthesi

Task-Relevant Representation Decoupling for Visual Reinforcement Learning Generalization

arXiv:2607.00796v1 Announce Type: new Abstract: Visual Reinforcement Learning (VRL) has achieved considerable success in solving control tasks. However, generalizing learned policies to new environmen

researcharxiv-cs-lg

Topological Void Analysis A Mathematical Framework for Systematic Technical Innovation Discovery in Knowledge Spaces

arXiv:2607.00005v1 Announce Type: cross Abstract: Identifying where to innovate in a dense technical domain - such as operating systems or hardware/software co-design - is fundamentally a search probl

researcharxiv-cs-ai

Understand to participate

I saw Geoffrey Litt speak at AIE yesterday, and one framing he used particularly resonated with me: Understand to participate Geoffrey was talking about the challenge of collaborating with coding agen

agentssimon-willison

Autoresearch: The feedback loop behind self-improving agents

Autoresearch describes a feedback mechanism where AI agents can evaluate their own outputs and use that introspection to iteratively improve their reasoning and decision-making capabilities. This conc

agentslatent-space

Beyond the Library: An Agentic Framework for Autoformalizing Research Mathematics

arXiv:2606.31134v1 Announce Type: new Abstract: While Large Language Models (LLMs) have demonstrated exceptional capabilities in mathematical reasoning, they frequently produce subtle errors that evad

agentsarxiv-cs-ai

Collaborative Knowledge Distillation via a Learning-by-Education Node Community

arXiv:2410.00074v2 Announce Type: replace Abstract: A novel Learning-by-Education Node Community framework (LENC) for Collaborative Knowledge Distillation (CKD) is presented, which facilitates continu

agentsarxiv-cs-lg

Elon Musk explains one of the most optimistic futures imaginable: Neuralink and Optimus restoring lost human abilities through real-world cy…

Elon Musk explains one of the most optimistic futures imaginable: Neuralink and Optimus restoring lost human abilities through real-world cyborg technology And the first people this could help are the

applicationselon-musk--x

Enhancing Graph Representations with Neighborhood-Contextualized Message-Passing

arXiv:2511.11046v3 Announce Type: replace-cross Abstract: Graph neural networks (GNNs) have become an indispensable tool for analyzing relational data. Classical GNNs are broadly classified into three

Tutorials

Improved Immiscible Diffusion: Accelerate Diffusion Training by Reducing Its Miscibility

arXiv:2505.18521v2 Announce Type: replace Abstract: The substantial training cost of diffusion models hinders their deployment. Immiscible Diffusion recently showed that reducing diffusion trajectory

tutorialsarxiv-cs-cv

Nazrin: An Atomic Neural Proof Automation Tactic in Lean 4

arXiv:2602.18767v3 Announce Type: replace-cross Abstract: In Machine-Assisted Theorem Proving, a theorem proving agent searches for a sequence of expressions and tactics that can prove a statement in

agentsarxiv-cs-lg

OpenLife: Toward Open-World Artificial Life with Autonomous LLM Agents

arXiv:2606.31046v1 Announce Type: new Abstract: Artificial life has explored life-like behavior on many computational substrates, but mostly in researcher-designed closed worlds. We argue that large l

agentsarxiv-cs-ai

Resolving superposition in AI for interpretability and cross-modal alignment in patient-neuronal images

arXiv:2606.31394v1 Announce Type: cross Abstract: Artificial intelligence is transforming our capability to solve biological challenges. In dimensionality bottleneck regimes exacerbated by high-dimens

Robustness of neural networks to random noise perturbations of their inputs

arXiv:2606.31581v1 Announce Type: new Abstract: We investigate the problem of the robustness of a trained neural network to the perturbation of its input values. More specifically, we examine the inte

applicationsarxiv-cs-lg

Robustness of Robotic Manipulation: Foundations and Frontiers

arXiv:2606.31494v1 Announce Type: cross Abstract: Humans and animals exhibit remarkable robustness in physical manipulation, yet robots remain far behind. Progress toward human-level manipulation robu

Size Doesn't Matter: Cosine-Scored Sparse Autoencoders

arXiv:2606.15054v2 Announce Type: replace Abstract: Sparse autoencoders (SAEs) detect features via inner product, so a feature's activation scales with both its directional alignment and the input's n

The Quadruped Soft Tail: Compliant Grasping and Swabbing for Contamination Surveys in Harsh Environments

arXiv:2606.30900v1 Announce Type: new Abstract: Beryllium contamination surveys in radioactive areas are challenging for robots in environments cluttered with cables and electronics. To address this p

researcharxiv-cs-ro

TotalFM: An Organ-Separated 3D-CT Foundation Model Leveraging Large-Scale Routine Clinical Radiology Data

arXiv:2601.00260v2 Announce Type: replace Abstract: While foundation models in radiology are expected to be applied to various clinical tasks, computational cost constraints remain a major challenge w

researcharxiv-cs-cv

A causal modeling perspective on decision theory

arXiv:2606.29911v1 Announce Type: new Abstract: Decision theory provides a formal framework for how agents should make choices under uncertainty, drawing on ideas from philosophy, probability, and cau

A Knowledge Theory of Capital:The Value of Natural and Artificial Intelligence, Volume 1

arXiv:2606.18288v2 Announce Type: replace-cross Abstract: This volume develops a knowledge theory of capital for economies in which productive capacity increasingly resides in software, data, models,

applicationsarxiv-cs-ai

Analyzing Defensive Misdirection Against Model-Guided Automated Attacks on Agentic AI Systems

arXiv:2606.20470v2 Announce Type: replace-cross Abstract: Agentic AI systems increasingly rely on language-model components to interpret instructions, process external data, invoke tools, and coordina

Attribution Graphs and Causal Probing for Mechanistic Discovery and Bias Repair in Multimodal Generative Learning

arXiv:2510.12957v4 Announce Type: replace-cross Abstract: We treat the internals of generative models as mechanistic objects rather than black boxes. We introduce extbf{Attribution Graphs} (AGs), whic

Bringing speed and strong cost performance to the market with Gemini Omni Flash and Nano Banana 2 Lite

model-releasesgoogle-cloud-ai

Great creative happens when your tools move at the speed of your ideas. To help you create rich, reliable experiences while reducing regeneration time and costs, we’re adding two new models to Gemini

Tutorials

Building artificial intelligence virtual tissue (AIVT) for tissue state representation, feature prediction, and dynamic simulation

arXiv:2606.29883v1 Announce Type: new Abstract: Modeling tissue states and their transitions is essential for understanding tissue homeostasis in health and pathological remodeling in disease. However

tutorialsarxiv-cs-cv

Local Ai

Can Machines Really See Objects in Images? A Study Based on Syntactic Distance and Visual Self-Referential Instances

arXiv:2606.29416v1 Announce Type: cross Abstract: Can a vision model truly see an object, or does it only fit surface-level visual cues? Following Wittgenstein's view that the limits of language are t

local-aiarxiv-cs-ai

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Cute illustrations made by @bclavie giving a talk at @aiDotEngineer @mixedbreadai “Code is knowledge but knowledge is not code”

This post references a talk given by @bclavie at an AI engineer event hosted by Mixed Bread AI, featuring cute illustrations and exploring the distinction between code as a form of knowledge represent

toolsswyx--x

Defeat Devices in AI Systems

arXiv:2606.28863v1 Announce Type: cross Abstract: AI systems increasingly exhibit behavior that differs systematically between evaluation and deployment contexts. Alignment faking, sandbagging, benchm

Dynamic Parsing and Updating Natural Language Specification using VLMs for Robust Vision-Language Tracking

arXiv:2606.29357v1 Announce Type: cross Abstract: Vision-language tracking guided by natural language specifications leverages high-level semantic cues of target objects to substantially boost trackin

EventVLA: Event-Driven Visual Evidence Memory for Long-Horizon Vision-Language-Action Policies

model-releasesarxiv-cs-cv

arXiv:2606.20092v2 Announce Type: replace Abstract: Memory remains a critical bottleneck for long-horizon robotic manipulation, as standard Vision-Language-Action (VLA) policies often fail when task-r

Expert-guided Clinical Text Augmentation via Query-Based Model Collaboration

arXiv:2509.21530v2 Announce Type: replace Abstract: Data augmentation is a widely used strategy to improve model robustness and generalization by enriching training datasets with synthetic examples. W

Exploration and Online Transfer with Behavioral Foundation Models

arXiv:2606.29980v1 Announce Type: new Abstract: Zero-shot Transfer in Reinforcement Learning (RL) aims to train an agent that can generate optimal policies for any reward function, without additional

Exploring the Value of Diverse LLM Explanations in Introductory Programming

arXiv:2606.28882v1 Announce Type: cross Abstract: Large Language Models (LLMs) have shown the potential to generate code explanations that surpass those of peers in quality, offering promising opportu

applicationsarxiv-cs-ai

Few-Shot Domain Incremental Learning via Continual Vision-Language Consolidation

arXiv:2606.30190v1 Announce Type: cross Abstract: Existing domain-incremental learning (DIL) strategies call for massive amounts of data to adapt to new domains and suffer from the overfitting problem

From Regulatory Approvals to Patents: Cross-Domain Linking for Cardiovascular Device Traceability

arXiv:2606.28353v1 Announce Type: cross Abstract: Linking FDA-approved medical devices to their underlying United States Patent and Trademark Office (USPTO) patents enables critical applications such

Gradient boosting with vector-valued leafs

arXiv:2606.29326v1 Announce Type: cross Abstract: Gradient boosting in the form of decision tree ensembles has successfully been applied to a variety of problems using simple objective functions based

researcharxiv-cs-lg

ISAC: Training-Free Instance-to-Semantic Attention Control for Multi-Instance Generation

arXiv:2505.20935v3 Announce Type: replace Abstract: Recent open-weight text-to-image (T2I) diffusion models still struggle with multi-instance prompts, often omitting or merging instances and mixing s

researcharxiv-cs-cv

Learned Coordination Conventions in Cooperative MARL: Measuring the Translation Gap Between Theory-Informed Roles and Learned Routing

arXiv:2606.29541v1 Announce Type: new Abstract: Role-semantic assignments provide priors over how heterogeneous agents may coordinate, but cooperative MARL systems instead settle on conventions throug

Tools

Loops! @swyx

This post from Swyx likely discusses loops in the context of web development, programming patterns, or a specific framework/tool. Without access to the full content, it appears to be a technical post

toolsswyx--x

LoRAShield: Data-Free Editing Alignment for Secure Personalized LoRA Sharing

arXiv:2507.07056v2 Announce Type: replace-cross Abstract: The proliferation of Low-Rank Adaptation (LoRA) models has democratized personalized text-to-image generation, enabling users to share lightwe

Meta-learning as a principle for human-like visual representations

arXiv:2606.28399v1 Announce Type: new Abstract: The structure of human visual representations underpins our capacity for adaptive behaviour. While pretrained neural networks model human visual represe

safetyarxiv-cs-cv

MOAR Planner: Multi-Objective and Adaptive Risk-Aware Path Planning for Infrastructure Inspection with a UAV

arXiv:2606.30575v1 Announce Type: new Abstract: The problem of autonomous navigation for UAV inspection remains challenging as it requires effectively navigating in close proximity to obstacles, while

safetyarxiv-cs-ro

Modelling Human Values for Value-Aware Multi-Agent Systems

arXiv:2402.06359v2 Announce Type: replace Abstract: One of today's most pressing societal challenges is building AI systems whose behaviour, or the behaviour it enables within communities of interacti

MOSAIC: Orchestrating Collaborative Knowledge Tracing with Hierarchical Semantic Alignment

arXiv:2606.29049v1 Announce Type: new Abstract: Knowledge Tracing (KT) is important for personalized education but traditionally suffers from two key limitations: a reliance on shallow ID-based repres

Local Ai

Multimodal and Multiscale Spatial-Temporal Semantic Search and Recommendation with AI Foundation Models

arXiv:2606.28369v1 Announce Type: cross Abstract: Semantic search and recommendation of similar documents, such as news and reports about unusual environmental events (e.g., a dead whale washed ashore

local-aiarxiv-cs-ai

Local Ai

Neural Gate: Mitigating Privacy Risks in LVLMs via Neuron-Level Gradient Gating

arXiv:2603.12598v2 Announce Type: replace Abstract: Large Vision-Language Models (LVLMs) have shown remarkable potential across a wide array of vision-language tasks, leading to their adoption in crit

local-aiarxiv-cs-cv