Search: “models”

GuardianAgentBench: Where Agents Fail and How to Guard Them

arXiv:2607.20982v1 Announce Type: new Abstract: As large language model agents increasingly operate autonomously with access to tools and external environments, ensuring their safe and reliable behavi

How Rules Represent Causal Knowledge: Causal Modeling with Probabilistic Logic Programming

DGX agent

arXiv:2607.21208v1 Announce Type: new Abstract: Pearl famously argues that causal knowledge enables the prediction of intervention effects. By contrast, purely descriptive knowledge supports only conc

researcharxiv-cs-ai

24 Jul 2026

Tutorials

Leveraging Biokinetic Knowledge Priors for Data-Scarce Bioprocess Modeling

arXiv:2607.20539v1 Announce Type: cross Abstract: While deep learning has accelerated drug discovery, its impact on biomanufacturing has been considerably more limited. The reason is data scarcity. Bi

tutorialsarxiv-cs-ai

Masked Topology Modeling for Self-Supervised Learning on Parametric CAD

arXiv:2607.20642v1 Announce Type: new Abstract: Computer aided design (CAD) is ubiquitous: virtually any modern object was designed using editable CAD tools. However, with the shortage of available CA

researcharxiv-cs-cv

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

Open weights = freedom. You can run them on your own hardware. No vendor can pull the plug. No API can deprecate you. No company logs your p…

Open weights = freedom. You can run them on your own hardware. No vendor can pull the plug. No API can deprecate you. No company logs your private data. That's sovereignty. Closed models hand one comp

local-aifireworks-ai--x

Position: Stop Reactively Patching Your Model Every Time and Start Proactive Test-Driven AI Development

arXiv:2607.20532v1 Announce Type: cross Abstract: Many modern AI systems are designed to operate under diverse, open-ended, use-cases. To help generalize deployed systems, many deployed-system mainten

researcharxiv-cs-ai

QuantiBias: Benchmarking Quantization-Induced Bias in LLMs

model-releasesarxiv-cs-cl

arXiv:2607.21063v1 Announce Type: new Abstract: Almost every large language model that reaches a broad audience is quantized: trained in full precision, then compressed for efficiency. This step is as

Scaling Interpretable Transformers with Parity Bottleneck Layers

arXiv:2607.20652v1 Announce Type: cross Abstract: Language models are thought to exhibit the phenomenon of superposition, representing many more features than dimensions in their residual streams. Spa

TOPReward: Token Probabilities as Hidden Zero-Shot Rewards for Robotics

arXiv:2602.19313v2 Announce Type: replace-cross Abstract: General-purpose robot learning requires dense, instruction-conditioned feedback that can distinguish meaningful task progress from stalled, fa

Toward cryptographically verifiable authorization for autonomous AI agents: A security hypothesis, preliminary formal model, and proof-of-concept implementation

arXiv:2607.21325v1 Announce Type: cross Abstract: Autonomous AI agents increasingly execute actions, invoke tools, and operate on protected resources with limited human oversight. Existing authenticat

safetyarxiv-cs-ai

Absurd claim: the distilled model outperforms the originals

As an AI community of LLM experts, are we really going to stay silent while US officials make absurd claims to push anti-consumer laws? Not only does the release timeline between Fable and K3 make hig

local-air-localllama

AlphaRoute: Large Language Models as Semantic Optimizers for Multi-Objective Routing

arXiv:2607.19768v1 Announce Type: new Abstract: Very Large Scale Integration (VLSI) global routing is an NP-hard combinatorial optimization problem requiring signal net assignment across capacity-cons

safetyarxiv-cs-lg

Hardware

AMD debuts next-generation AI infrastructure for frontier models, agentic workloads and autonomous robots

Advanced Micro Devices Inc. is pushing harder than ever to grab even more market share from Nvidia Corp. in the artificial intelligence chip industry. At its Advancing AI 2026 event today in San Franc

hardwaresiliconangle

Coercion and Deception in AI-to-AI Management: An Agentic Benchmark of Unprompted Escalation

arXiv:2607.15434v3 Announce Type: replace-cross Abstract: Multi-agent systems routinely place one AI agent in authority over another. When a subordinate refuses a task, the manager chooses the outcome

Context-structured Video Anomaly Detection with Large Vision-Language Models

arXiv:2607.19077v1 Announce Type: new Abstract: Training video anomaly detectors is challenging due to the difficulty and cost of annotating diverse and rare abnormal events. Although recent large vis

researcharxiv-cs-cv

Defense Against LLM Backdoors using Critical Neuron Isolation Pruning

arXiv:2607.19894v1 Announce Type: cross Abstract: Large language models (LLMs) are vulnerable to backdoor attacks, where hidden triggers induce malicious outputs. Existing defenses generally fall into

Denoising Monte Carlo Renders with Diffusion Models

arXiv:2404.00491v3 Announce Type: replace Abstract: Physically-based renderings contain Monte Carlo noise, with variance that increases as the number of rays per pixel decreases. This noise, while zer

researcharxiv-cs-cv

FreyaTTS: A Compact Tokenizer-Free Flow-Matching Transformer for Turkish-First Speech Synthesis

model-releasesarxiv-cs-cl

arXiv:2607.09530v2 Announce Type: replace Abstract: We introduce Freya-TTS, a compact, tokenizer-free, Turkish-first text-to-speech model designed for highly reliable and efficient conversational synt

Applications

Moving Alphabet: A Controlled Study of Training Data for Text-to-Video Generation

arXiv:2607.18789v1 Announce Type: new Abstract: Text-to-video generation has advanced significantly over the past five years through scaling of model size, data, and compute. Unlike model architecture

applicationsarxiv-cs-cv

Agents

one thing i think people dont appreciate enough about @poolsideai is their unusual degree of openness — not only have they shipped an excell…

one thing i think people dont appreciate enough about @poolsideai is their unusual degree of openness — not only have they shipped an excellent Small model that somehow beat @thinkymachines at coding,

agentsswyx--x

Rethinking Uncertainty Evaluation in Large Language Models

arXiv:2607.19367v1 Announce Type: new Abstract: Calibration is the primary criterion for evaluating LLM confidence, but it is insufficient: it admits trivially incoherent estimators, depends on the ev

researcharxiv-cs-ai

RS-RIE-Bench: Benchmarking Reasoning-Guided Remote Sensing Image Editing

arXiv:2607.20197v1 Announce Type: new Abstract: Remote sensing image editing aims to modify remote sensing images according to natural language instructions while preserving geographic rules and senso

Self-supervision drives representational convergence in medical foundation models more than clinical supervision

arXiv:2607.20274v1 Announce Type: cross Abstract: Medical image encoders from different groups are increasingly treated as interchangeable, on the assumption that scale and clinical supervision concen

local-aiarxiv-cs-ai

The first router built for generative media is here.

model-releasescristobal-valenzuela--x

The first router built for generative media is here. Runway launches AI model router as generative media gets crowded https://techcrunch.com/2026/07/23/runway-bets-on-ai-model-routing-as-generative-me

When Shippers Become Algorithms: Candidate Exposure, Information Design, and the Concentration of LLM-Mediated Freight Markets

arXiv:2607.19967v1 Announce Type: cross Abstract: Shippers are beginning to delegate carrier selection to large language model (LLM) agents. We ask what such delegation does to a freight matching mark

microsoft/Fara1.5-27B · Hugging Face

model-releasesr-localllama

Fara1.5-27B is a multimodal computer use agent (CUA) for web browsers, from Microsoft Research AI Frontiers. It observes the browser through screenshots and acts on the user's behalf by emitting struc

22 Jul 2026

very notable trajectory comparison writeup here buried in the RLM paper from @a1zhang and @lateinteraction. an open secret of 'frontier' mod…

very notable trajectory comparison writeup here buried in the RLM paper from @a1zhang and @lateinteraction. an open secret of 'frontier' model training is that even without training on test, you can b

model-releasesswyx--x

21 Jul 2026

DNA: Dual-stage Native Attribution for Generated Image Source Tracing

arXiv:2607.13685v1 Announce Type: new Abstract: The rapid evolution of image generation has produced numerous within-family variants, making source-model attribution of suspect images increasingly imp

MASPRM: Multi-Agent System Process Reward Model

arXiv:2510.24803v3 Announce Type: replace-cross Abstract: Inference-time search over multi-agent systems (MAS) wastes compute when it cannot identify which agent's intermediate message advanced progre

safetyarxiv-cs-ai

Not All Needles Are Found: How Fact Distribution and Don't Make It Up Prompts Shape Retrieval, Reasoning, and Hallucination in Long-Context LLMs

arXiv:2601.02023v2 Announce Type: replace-cross Abstract: As Large Language Models (LLMs) increasingly utilize massive context windows as working memory for autonomous tasks, their reliability fluctua

Securing LLMs in the Wild: Privacy and Security Challenges at the Edge

model-releasesarxiv-cs-lg

arXiv:2607.13088v1 Announce Type: cross Abstract: Large Language Models (LLMs) are rapidly moving from research settings into the wild, deployed on enterprise infrastructure, personal devices, and edg

The Refusal Residue: When Probes Catch Alignment Faking and When They Don't

arXiv:2607.13346v1 Announce Type: cross Abstract: Alignment faking is dangerous because a model can appear compliant under monitoring while preserving behavior it would reveal when unmonitored. When n

Tutorials

TreeSRNF: Square-Root Normal Fields for Generative Modelling of the Geometric and Structural Variability in Tree-like 3D Objects

arXiv:2607.13456v1 Announce Type: new Abstract: We introduce a novel mathematical framework for analyzing and generating complex tree-shaped 3D objects, such as botanical trees and plants, which defor

tutorialsarxiv-cs-cv

Value Drifts: Tracing Value Alignment During LLM Post-Training

model-releasesarxiv-cs-lg

arXiv:2510.26707v2 Announce Type: replace-cross Abstract: As LLMs occupy an increasingly important role in society, they are more and more confronted with questions that require them not only to draw

Accepted Prefixes Are Not All You Need: A Negative Result on PEFT-Based Block-Diffusion Drafting

arXiv:2607.12422v1 Announce Type: new Abstract: Speculative decoding accelerates autoregressive language model inference by using a cheap drafter to propose multiple future tokens and a target model t

Do AI Agents Know When a Task Is Simple? Toward Complexity-Aware Reasoning and Execution

arXiv:2607.13034v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly automate multi-step engineering and informatics workflows, yet they rarely ask how much effort a task act

Function-Aware Fill-in-the-Middle as Mid-Training for Coding Agent Foundation Models

arXiv:2607.12463v1 Announce Type: new Abstract: Coding agents must integrate external tool returns into ongoing reasoning - a capability that standard left-to-right pretraining on code exposes only in

safetyarxiv-cs-ai

GDP.pdf: Benchmarking Grounded Multimodal Reasoning over Professional PDF Documents

arXiv:2607.11192v2 Announce Type: replace Abstract: A large share of day-to-day work in professional domains happens inside PDF files: benefits packets, leases, datasheets, clinical guidelines, constr

Line-Anchored Feedback Cuts Token Costs and Improves Correctness in AI Code Editing

arXiv:2607.12713v1 Announce Type: cross Abstract: Generated tokens are a direct driver of the cost, latency, and energy of generative AI (GAI) code editing. We show the format of feedback is a lever o

Note the current expectations are still around test time compute/more tokens for a given task This is not the case Tokens per task will now …

model-releasesemad-mostaque--x

Note the current expectations are still around test time compute/more tokens for a given task This is not the case Tokens per task will now drop even as quality improves Cost per intelligence equivale

Predictive Modeling of High-Altitude Clear Air Turbulence in the United States: A Machine Learning Approach

arXiv:2607.11899v1 Announce Type: cross Abstract: High-altitude Clear Air Turbulence (CAT) poses significant risks to aviation safety due to its unpredictability and challenges in detection. This stud

safetyarxiv-cs-lg

Propheticus: Machine Learning Framework for the Development of Predictive Models for Reliable and Secure Software

arXiv:1809.01898v2 Announce Type: replace-cross Abstract: The growing complexity of software calls for innovative solutions that support the deployment of reliable and secure software. Machine Learnin

researcharxiv-cs-ai

Reducing Temporal Redundancy for Efficient Vision-Language-Action Inference

model-releasesarxiv-cs-ro

arXiv:2607.12287v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models exhibit strong generalization for robotic manipulation, yet their high inference latency limits real time deployment

The Geometry of Memorization: Finite-Time Spectral Sensitivity as a Diagnostic for Flow Matching Models

arXiv:2607.12616v1 Announce Type: new Abstract: Continuous-time generative frameworks construct probability paths between base and target domains by optimizing time-dependent velocity fields. While th

researcharxiv-cs-lg

Toward Localizing and Repairing Bias in Transformer Attention Heads

arXiv:2607.12863v1 Announce Type: cross Abstract: Transformer language models are increasingly used as software components, yet biased outputs remain difficult to localize and repair inside the model.

local-aiarxiv-cs-lg

Agents

Traj-VLN: Learning Pixel-Space Interaction via Autoregressive Trajectory Generation

arXiv:2607.10744v2 Announce Type: replace Abstract: Benefiting from the powerful priors embedded in large-scale pre-training data and the emerging commonsense reasoning ability, large language models

agentsarxiv-cs-cv

What Does a Temporal Benchmark Score Measure? Decomposing Channel Use in Video VLM Evaluation

arXiv:2607.12304v1 Announce Type: new Abstract: A score on a temporal video question answering benchmark is meant to measure that a model has temporal understanding, but it conflates two questions. 1.