Search: “papers”

Neat work on long-horizon agents. Splitting a hard task across agents is typically how standard multi-agent work. The usual design lets them…

Neat work on long-horizon agents. Splitting a hard task across agents is typically how standard multi-agent work. The usual design lets them exchange findings only at phase boundaries, through staged

model-releasesdair-ai--x

31 Jul 2026

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New research from Microsoft. This one is on training computer-use agents at scale. Recent pipelines generate synthetic environments in bulk,…

DGX agent

New research from Microsoft. This one is on training computer-use agents at scale. Recent pipelines generate synthetic environments in bulk, which moved the bottleneck from how many exist to what is i

model-releasesdair-ai--x

31 Jul 2026

Pramana: A Composable, Domain-Specific Backend for Empirical Networking Research

arXiv:2607.26352v1 Announce Type: cross Abstract: Networking research advances by turning hypotheses into empirical evidence, so accelerating it means reducing the lag between ideation (synthesizing a

31 Jul 2026

SciSchema.org: A Multidisciplinary Collection of Schemas for Structured Scientific Process Descriptions

arXiv:2607.27955v1 Announce Type: cross Abstract: Scientific processes are often described in heterogeneous article discourse, with details needed for comparison, reproducibility, reuse, and automatio

researcharxiv-cs-cl

31 Jul 2026

Actions Have Consequences: Detecting Outcome Performativity using Intervention Testing

arXiv:2607.26908v1 Announce Type: new Abstract: In many domains such as Palliative Care, Credit Assignment and Recommender Systems, predictions may causally influence the outcomes they predict. This p

applicationsarxiv-cs-lg

As the benchmarks that test frontier AI on get more complex, we are losing one of the most important aspects of benchmarking: comparisons to…

applicationsethan-mollick--x

As the benchmarks that test frontier AI on get more complex, we are losing one of the most important aspects of benchmarking: comparisons to humans Validated benchmarks need to have human (ideally mul

Automorphism-Induced Non-Canonicity in Top-k Explanations of Graph Neural Networks

model-releasesarxiv-cs-lg

arXiv:2607.26344v1 Announce Type: new Abstract: A gradient-based GNN explainer given a molecule with two chemically equivalent nitro groups assigns them attribution scores that are equal to the last b

Multi-Objective Compliance-Integrated Coevolution For Simulated And Real-World Deployment Of Multi-Robot Marine Autonomy

arXiv:2607.26279v1 Announce Type: new Abstract: Collaborative robots are well-suited to maritime missions that benefit from coordination, such as the exploration of unknown reef structures, inspection

safetyarxiv-cs-ro

Online Handwriting Trajectory Reconstruction from Kinematic Sensors using Temporal Convolutional Network

arXiv:2607.26733v1 Announce Type: new Abstract: Handwriting with digital pens is a common way to facilitate human-computer interaction through the use of Online Handwriting (OH) trajectory reconstruct

Scientific Knowledge Discovery in the Age of Large Language Models

arXiv:2607.26670v1 Announce Type: cross Abstract: The rapid growth of scholarly literature has made identifying relevant publications increasingly difficult, and conventional search systems still depe

researcharxiv-cs-cl

SciFigQual-Bench: A Benchmark for Scientific Figure Quality Assessment with Full-Manuscript Context

arXiv:2607.27084v1 Announce Type: new Abstract: Scientific images are the core elements of presenting experimental conclusions, elaborating system architecture, and supporting comparative arguments in

We have to be careful to not offload our understanding to agents. I think there is also a good opportunity to build agentic applications tha…

We have to be careful to not offload our understanding to agents. I think there is also a good opportunity to build agentic applications that encourage deeper understanding. For example, coding agents

agentsdair-ai--x

When benchmark inferences do not compose: Projectibility in AI evaluation

model-releasesarxiv-cs-lg

arXiv:2607.26159v1 Announce Type: cross Abstract: An AI benchmark result rarely reaches a consequential claim in one step. Evaluators generalize it to further cases, interpret it as evidence of capabi

AI Deployment and Cyber Governance Failures in Public-Sector Organizations: A Typological Analysis

arXiv:2607.25368v1 Announce Type: new Abstract: The intersection of artificial intelligence adoption, cybersecurity governance, and public sector institutional constraints has not been examined as a u

Context Assembly as the Controlled Variable: A Control-Theoretic View of Harness Policies for Frozen LLM Agents

arXiv:2607.25408v1 Announce Type: new Abstract: A growing body of 2026 work applies control theory to LLM agents: Lyapunov-certified stability for tool-mediated controllers (Prinos et al., 'Stable Age

safetyarxiv-cs-ai

Decision-Level Hijacking: Injecting Cognitive Bias into Large Language Models via Bit-Flip Attacks

model-releasesarxiv-cs-lg

arXiv:2607.25227v1 Announce Type: cross Abstract: Large Language Models (LLMs) have been widely applied in high-stakes decision-making scenarios such as corporate strategy, and users are increasingly

F(AI)2R: Who Did What, and Who Checked? Verifiable AI Provenance as an Executable Skill

arXiv:2607.25637v1 Announce Type: cross Abstract: F(AI)2R is FAIR research with AI in the loop, twice: an AI-assisted authoring pass and a machine-readable audit pass over every artefact. AI systems n

Finding Optimal Cost-Bounded Plan Reductions: Refined Model

arXiv:2607.25484v1 Announce Type: new Abstract: In some real applications a plan may later become unfeasible due to newly imposed budget constraints, yet, at the same time, using only the original act

Forgetting Is Not a Fix: Path Dependence in Sequential Engram Editing

arXiv:2607.24805v1 Announce Type: cross Abstract: AI Engram (Kwon et al., 2026) formalizes the four engram criteria of neuroscience as a constrained inverse problem in weight space and solves it close

researcharxiv-cs-lg

From CUDA to MLX: How K-Search Brings Decades of Kernel Expertise to Apple Silicon

model-releasesberkeley-ai-research

Figure 1: CUDA-to-MLX optimization translation map. CUDA optimization knowledge can be translated into architecture-native MLX strategies rather than copied instruction-for-instruction. We face a new

Game AI Not Fun? A Scoping Review and Meta-Analysis on the Differences in Enjoyment between Human and Computer Opponents

arXiv:2607.24749v1 Announce Type: cross Abstract: Although advancements in game character AI aim to enhance player engagement, evidence suggests that perceiving an opponent as artificial can diminish

Lowering the implementation barrier of neutral-atom quantum computing with agentic workflows

arXiv:2607.25834v1 Announce Type: cross Abstract: Quantum computers are moving from research laboratories to industrial machines accessible via the cloud and integrated into high-performance computing

Phase Structure in Rotary Attention: A Spectral Framework for Semantic Continuity and Execution-Boundary Governance

arXiv:2607.25507v1 Announce Type: new Abstract: Transformer language models are usually analyzed through vector geometry, yet ordered context and rotary position encoding introduce explicit phase stru

safetyarxiv-cs-cl

Local Ai

Understand Kimi K3 from first principles: a recommended order for anyone trying to understand this beast

Everyone is talking about Kimi K3, but if you jump straight into the technical report, you’ll quickly realize it’s standing on years of research -- just like any breakthrough is! If you want to unders

local-air-localllama

// Unfolding Sub-Agents for Long-Horizon ML Engineering // Watch a single agent work a machine learning engineering task for six hours you s…

// Unfolding Sub-Agents for Long-Horizon ML Engineering // Watch a single agent work a machine learning engineering task for six hours you see issues like context fills with stack traces, dead experim

agentsdair-ai--x

Across eight case studies spanning industry and academia, we explore what this shift means for scientific computing—and why human verificati…

Across eight case studies spanning industry and academia, we explore what this shift means for scientific computing—and why human verification, stewardship, and long-term maintenance matter. https://o

agentsopenai--x

An Ontology for Machine Learning Interatomic Potentials

model-releasesarxiv-cs-ai

arXiv:2607.23219v1 Announce Type: new Abstract: Machine learning interatomic potentials (MLIPs) approximate quantum-mechanical energies and forces---conventionally computed by density functional theor

Everything you need to know about Kimi K3 with @Kimi_Moonshot and @togethercompute team. If you're looking into evaling and building with Ki…

applicationstogether-ai--x

Everything you need to know about Kimi K3 with @Kimi_Moonshot and @togethercompute team. If you're looking into evaling and building with Kimi K3 I would not miss this one! Kimi K3 has everyone’s atte

Tutorials

From Machine Learning to Large-Scale EO Products: Best Practices for Making Maps

arXiv:2607.24532v1 Announce Type: new Abstract: Recent years have seen a rapid expansion in the production of large-scale geospatial maps derived from Earth observation (EO) data, driven largely by ad

tutorialsarxiv-cs-lg

Grading the Narrators: An Isnad-Rijal Framework for Claim-Level Provenance in Multi-Agent Knowledge Systems

arXiv:2607.24117v1 Announce Type: new Abstract: Modern multi-agent knowledge systems increasingly accumulate knowledge through chains of autonomous transformations rather than direct retrieval. Existi

MATS: A novel multi-modality multi-task learning framework for 3D perception in autonomous driving

arXiv:2607.24224v1 Announce Type: new Abstract: Multi-modality data from different sensors provides rich complementary information for 3D perception, becoming an essential component in reliable autono

Phenology-based learning framework for yield estimation and harvest forecasting of raspberry fruits

arXiv:2411.00967v2 Announce Type: replace Abstract: The future of agriculture is intertwined with automation. Accurate fruit detection, yield estimation, and harvest time prediction are crucial for ef

Visible-Light Imaging Diagnosis of Neutral Particle Emission Tomography in the Tokamak Divertor: An Efficient Transformer-based Surrogate Model

model-releasesarxiv-cs-ai

arXiv:2607.22704v1 Announce Type: cross Abstract: Nuclear fusion has made significant progress in recent years and is expected to become one of the most important pathways to addressing global energy

Token-Operations-Oriented Inference Optimization Techniques for Large Models

arXiv:2606.20295v2 Announce Type: replace-cross Abstract: Large model inference optimization serves as a key foundation for supporting the scalable, low-cost, and highly stable operation of large mode

applicationsarxiv-cs-cl

27 Jul 2026

Recent discussions about open-sourcing make me feel that I should go back and revisit these important open-source works in representation le…

Recent discussions about open-sourcing make me feel that I should go back and revisit these important open-source works in representation learning that pushed the field forward and eventually made vis

researchyann-lecun--x

26 Jul 2026

We compared different LLMs on IMO 2026 [R]

model-releasesr-machinelearning

There are a few reasons why problems from International Mathematical Olympiad function as a good benchmark for LLMs: - The problems are new, not included in the training data of any model - Hard math

26 Jul 2026

Hardware

Can AMD break the CUDA Moat? AMD Advancing AI 2026

AMD’s AI accelerator software stack has progressed sharply, moving from a 0 % chance of catching Nvidia’s CUDA moat in early 2025 to a “great chance” of success by July 2026 after leadership changes a

hardwaresemianalysis

Diffusion LLMs can now handle real agentic work. LLaDA 2.2 is the first large-scale diffusion LLM built to operate as a real agent, planning…

Diffusion LLMs can now handle real agentic work. LLaDA 2.2 is the first large-scale diffusion LLM built to operate as a real agent, planning, calling tools, and self-correcting across long multi-turn

agentsdair-ai--x

Ha! It did it: 'We introduce BenchBenchBenchBenchBench (BBBBB), an executable benchmark of AI-authored conformance suites for benchmark-eval…

model-releasesethan-mollick--x

Ha! It did it: 'We introduce BenchBenchBenchBenchBench (BBBBB), an executable benchmark of AI-authored conformance suites for benchmark-evaluation metrics' I really thought it would treat 'now do benc

Nvidia, other tech giants caution against open-source AI ban in open letter

model-releasessiliconangle

A group of tech firms has released an open letter that calls on policymakers not to ban open-source artificial intelligence models. The development follows a report that some Trump administration offi

As a joke I prompted Codex 'Build and run BenchBench, a benchmark of now good ai is at creating benchmarks. then figure out what benchbenchb…

model-releasesethan-mollick--x

As a joke I prompted Codex 'Build and run BenchBench, a benchmark of now good ai is at creating benchmarks. then figure out what benchbenchbench is and run that. and then write benchbenchbench up as a

Fizgig Krea 2 training features update

https://github.com/shootthesound/Fizgig Intelligent trainer - Per-image loss tracking with self-adapting training runs — every image gets its own verdict (easy / suspect / stuck / exhausted) and its o

safetyr-stablediffusion

Tutorials

NeuraLSP: A Neural Spectral Preconditioner for Accelerating PDE Solvers

arXiv:2601.20174v3 Announce Type: replace-cross Abstract: Solving large-scale sparse linear systems originating from partial differential equations (PDEs) is a fundamental topic in high-performance sc

tutorialsarxiv-cs-ai

Nvidia releases Qwen-Image-Flash

model-releasesr-stablediffusion

'The NVIDIA Qwen-Image-Flash model generates images from text prompts using a four-step, DMD2-distilled version of Qwen/Qwen-Image. The distillation used DMD2 from NVIDIA FastGen, NVIDIA Model Optimiz

Scientific exploration, collaboration and labor division in the large language model era

arXiv:2607.20923v1 Announce Type: cross Abstract: Large language models (LLMs) have rapidly and significantly entered scientific workflows, but it remains unclear how their diffusion is associated wit

Semantic Field Theory: Historical Origin, Higher-Order Interaction, and Stabilized Semantic Inference

arXiv:2607.20451v1 Announce Type: new Abstract: Semantic Field Theory (SFT) has developed from a philosophical critique of strong anti-formalist readings of language games into a proposed computationa

researcharxiv-cs-cl

T-STAR: A Large-Scale Benchmark for Spatio-Temporal Panoptic Scene Graph Generation in Satellite Video

arXiv:2607.21228v1 Announce Type: new Abstract: Structured understanding of satellite video is essential for advancing dynamic geospatial scene analysis from low-level perception to high-level cogniti

The Storyteller in the Model: Narrative Pattern Inheritance, Escalation Dynamics, and Alignment Governance in LLMs

arXiv:2607.20449v1 Announce Type: cross Abstract: LLMs are trained predominantly on human-authored text, yet the structural and narrative conventions embedded in that text are rarely examined as a sou

safetyarxiv-cs-ai