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This is a good clip that shows a few layouts. I'm pretty happy with this, maybe the slide layout could be a bit different and I'm curious ho…

This is a good clip that shows a few layouts. I'm pretty happy with this, maybe the slide layout could be a bit different and I'm curious how it will alternate between camera cuts. That's all for now,

model-releasesthariq--x

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Model Releases

this is a great approach, seeing this more @flymy_ai also does this when you build an agent via their api, they'll build a deterministic reu…

DGX agent

this is a great approach, seeing this more @flymy_ai also does this when you build an agent via their api, they'll build a deterministic reusable workflow, except for where you need models we built th

model-releasesyohei-nakajima--x

7 Jul 2026

This is a key reason I don’t expect the flow of frontier open weights models to continue indefinitely, or even for very much longer. https:/…

applicationsethan-mollick--x

This is a key reason I don’t expect the flow of frontier open weights models to continue indefinitely, or even for very much longer. https://www.reuters.com/world/beijing-is-looking-curbing-overseas-a

Agents

This is the great thing about OpenWiki! It’ll maintain the docs for you automatically. Just setup a GitHub to run: openwiki —update and it’l…

This is the great thing about OpenWiki! It’ll maintain the docs for you automatically. Just setup a GitHub to run: openwiki —update and it’ll put up a PR once a day with changes / additions to your me

agentsharrison-chase--x

Hardware

This is what latency optimization looks like below the API 👇 Together ATLAS, NVIDIA Blackwell, CUDA, TensorRT-LLM, Dynamo, and custom kerne…

This is what latency optimization looks like below the API 👇 Together ATLAS, NVIDIA Blackwell, CUDA, TensorRT-LLM, Dynamo, and custom kernels all working together to make inference faster for users. P

hardwaretogether-ai--x

This is what stealing your data looks like

This post from Cohere likely illustrates or visualizes data theft methods, showing how personal or organizational data can be compromised or misused by bad actors. It probably demonstrates common data

model-releasescohere--x

This race car is made from plant fibers, volcanoes, ... and seawater?

Lola has replaced the original fiberglass bodywork with a composite system made from plant fibers and basalt fibers from volcanic rock, held together by plant-based resin from sugar cane. The vehicle'

applicationsars-technica

ThreatVisionAI: A Hybrid CNN-ViT Framework for Image-Based Malware Classification

arXiv:2607.03653v1 Announce Type: cross Abstract: Traditional malware detection methods struggle to generalize to obfuscated or previously unseen threats. This paper introduces ThreatVisionAI, a hybri

Three-Phase Evaluation of AI-Assisted Software Development Life Cycle

arXiv:2607.05125v1 Announce Type: cross Abstract: This paper presents an exploratory evaluation of how increasing levels of AI autonomy affect software development productivity, requirement adherence,

TIER: Trajectory-Invariant Explanation Regularization for Membership Privacy

arXiv:2607.02903v1 Announce Type: cross Abstract: Explainability is central to building trustworthy AI, yet explanation interfaces can inadvertently provide adversaries with an expanded privacy-relate

Tight Stability Bounds for Robust Distributed Learning: Byzantine Failures Hurt Generalization More than Data Poisoning

arXiv:2506.18020v3 Announce Type: replace Abstract: Robust distributed learning algorithms aim to maintain reliable performance despite the presence of misbehaving workers. Such misbehaviors are commo

Tightening the Score Matching Gap for Diffusion Models

arXiv:2607.04442v1 Announce Type: cross Abstract: Diffusion models (DMs) are a state-of-the-art generative method to approximately sample from an unknown distribution. Their training and evaluation pr

Tile-Level Activation Overlap for Efficient LLM Inference

model-releasesarxiv-cs-lg

arXiv:2607.02521v1 Announce Type: cross Abstract: SwiGLU is the dominant MLP activation in modern large language models, yet its intermediate tensor materialization costs 9-37% of MLP execution time.

TimeThink: Reasoning with Time for Video LLMs

arXiv:2607.05089v1 Announce Type: new Abstract: Video reasoning requires models to identify and verify temporally localized evidence within long video sequences. Recent Video Large Language Models (Vi

researcharxiv-cs-cv

TiROD: Tiny Robotics Dataset and Benchmark for Continual Object Detection

arXiv:2409.16215v4 Announce Type: replace-cross Abstract: Detecting objects with visual sensors is crucial for numerous mobile robotics applications, from autonomous navigation to inspection. However,

tldr of thariq's AIEWF keynote https://latent.space/p/ainews-the-field-guide-to-fable (more in today's ainews issue)

tldr of thariq's AIEWF keynote https://latent.space/p/ainews-the-field-guide-to-fable (more in today's ainews issue) my keynote at AI Engineer World Fair: “A Field Guide to Fable” is live on YouTube!

tutorialsswyx--x

Safety

TokAN: Accent Normalization Using Self-Supervised Speech Tokens

arXiv:2607.03928v1 Announce Type: cross Abstract: Accent normalization (AN) seeks to convert non-native (L2) accented speech into standard (L1) speech while preserving speaker identity. The current te

safetyarxiv-cs-ai

Token-Based Affordance Grounding with Large Vision-Language Models

arXiv:2607.03595v1 Announce Type: cross Abstract: Affordance grounding aims to localize image regions that support a specific action, serving as a core capability for physical intelligence and embodie

Token Communications: A Large Model-Driven Framework for Cross-modal Context-aware Semantic Communications

arXiv:2502.12096v5 Announce Type: replace-cross Abstract: In this paper, we introduce token communications (TokCom), a large model-driven framework to leverage cross-modal context information in gener

tutorialsarxiv-cs-cv

Token-level Response-visual Attention Guidance for Multimodal LLMs Knowledge Distillation

arXiv:2607.02593v1 Announce Type: cross Abstract: While knowledge distillation (KD) is widely adopted for training lightweight models by leveraging supervision from larger teacher models, relying sole

researcharxiv-cs-cl

TokSuite: Measuring the Impact of Tokenizer Choice on Language Model Behavior

model-releasesarxiv-cs-cl

arXiv:2512.20757v2 Announce Type: replace Abstract: Tokenizers provide the fundamental basis through which text is represented and processed by language models (LMs). Despite the importance of tokeniz

ToolFailBench: Diagnosing Tool-Use Failures in LLM Agents

arXiv:2607.04686v1 Announce Type: cross Abstract: Tool calling is central to modern language model agents, but aggregate benchmark scores often hide where tool use fails. A model that never calls a ne

Topological data analysis using persistent discrete homology

arXiv:2506.15020v2 Announce Type: replace-cross Abstract: We propose persistent discrete homology as a tool for topological data analysis and discuss its advantages over the existing methods. In parti

Topological Shape Representation for Aneurysm -- Bifurcation Detection

arXiv:2607.05317v1 Announce Type: cross Abstract: Automated detection of intracranial aneurysms (IAs) from CT angiography (CTA) is severely hindered by high false-positive rates. Convolutional neural

Topology-Driven Transferability Estimation for 3D Medical Vision Foundation Models

arXiv:2607.04199v1 Announce Type: new Abstract: The growing number of medical vision foundation models highlights the need for effective model selection. However, mainstream selection methods rely on

TORINO: Token Reduction via Interpretable Concept Overlap in Vision-Language Models

arXiv:2607.04593v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have demonstrated impressive capabilities across different tasks, but their computational cost is dominated by the large

Toward Efficient Agents: Memory, Tool learning, and Planning

arXiv:2601.14192v2 Announce Type: replace Abstract: Recent years have witnessed increasing interest in extending large language models into agentic systems. While the effectiveness of agents has conti

Toward Efficient Uncertainty in LLMs through Evidential Knowledge Distillation

arXiv:2507.18366v2 Announce Type: replace Abstract: Accurate uncertainty quantification remains a key challenge for standard LLMs, prompting the adoption of Bayesian and ensemble-based methods. Howeve

Toward Personalized Social Robots for Child Well-being: Data Requirement Principles from a Recommender-System Perspective

arXiv:2607.05110v1 Announce Type: cross Abstract: Social robots are increasingly deployed in clinical settings to support the well-being of children, where effective support must be personalized to ea

researcharxiv-cs-ro

Toward Trustworthy Large Language Model Agents in Healthcare

arXiv:2607.05055v1 Announce Type: new Abstract: Healthcare appointment scheduling remains a persistent operational bottleneck, driven by manual coordination, fragmented legacy systems, and high admini

Safety

Towards Data-Driven Metrics for Social Robot Navigation Benchmarking

arXiv:2509.01251v3 Announce Type: replace Abstract: This paper presents a joint effort towards the development of a data-driven Social Robot Navigation metric to facilitate benchmarking and policy opt

safetyarxiv-cs-ro

Towards Digital Preservation of Efik: TTS for a Low-Resource African Language

arXiv:2607.04515v1 Announce Type: new Abstract: Efik, a tonal language spoken by about 3 million second language speakers and 1.5 million native speakers in Southeastern Nigeria, remains underrepresen

researcharxiv-cs-cl

Towards Diverse and Comprehensive Benchmarks for Mutual Information Estimation

arXiv:2607.03487v1 Announce Type: cross Abstract: Mutual information (MI) estimation is a central problem in machine learning and statistics; however, existing benchmarks typically evaluate estimators

applicationsarxiv-cs-ai

Agents

Towards Mitigation of Hallucination for LLM-empowered Agents: Progressive Generalization Bound Exploration and Watchdog Monitor

arXiv:2507.15903v2 Announce Type: replace-cross Abstract: Empowered by large language models (LLMs), intelligent agents have become a popular paradigm for interacting with open environments to facilit

agentsarxiv-cs-ai

Towards Open-World Referring Expression Comprehension: A Benchmark with Training-free Multi-task Consistency Checker

arXiv:2605.25706v2 Announce Type: replace Abstract: Referring expression comprehension (REC) aims to localize a target object within an image based on a given expression. Although recent advances in v

Towards Personalized Differentially Private Learning for Decentralized Local Graphs

arXiv:2607.04777v1 Announce Type: new Abstract: Graph-structured data is increasingly generated and stored in decentralized environments, such as social platforms, mobile applications, and edge networ

applicationsarxiv-cs-lg

Towards Realistic Remote Sensing Dataset Distillation with Discriminative Prototype-guided Diffusion

arXiv:2601.15829v2 Announce Type: replace Abstract: Recent years have witnessed the remarkable success of deep learning in remote sensing image interpretation, driven by the availability of large-scal

Towards Reliable Local Security Agents: Verifiable Post-Training for Linux Privilege Escalation

arXiv:2603.17673v2 Announce Type: replace-cross Abstract: LLM agents are becoming increasingly important in the security domain, but leading systems are often closed-source, cloud-based, hard to repro

Towards Standardized Light Field Quality Assessment: Hybrid Subjective Benchmarking and Objective Metric Evaluation

arXiv:2607.03494v1 Announce Type: new Abstract: Benchmarking immersive media coding solutions, especially in the standardization context, requires reliable and reproducible subjective quality assessme

Towards transferable lightweight neuromorphic computing through a model-free temporal-switch framework

model-releasesarxiv-cs-lg

arXiv:2607.02608v1 Announce Type: cross Abstract: Lightweight neuromorphic computing offers a promising route to efficient AI, with particular benefits for resource-constrained edge deployments. Howev

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test

arXiv:2505.08814v3 Announce Type: replace-cross Abstract: Deep neural networks (DNNs) play a crucial role in the field of artificial intelligence, and their security-related testing has been a promine

TRACE: Capability-Targeted Agentic Training

arXiv:2604.05336v2 Announce Type: replace Abstract: Models often fail to complete agentic tasks because they lack core capabilities required by the target environment. However, mainstream approaches f

TRACER: Early Failure Detection for Task-Oriented Dialogue

arXiv:2607.03974v1 Announce Type: new Abstract: Task-oriented dialogue systems often fail before the final breakdown is obvious, but most evaluation only measures failure after the conversation has al

researcharxiv-cs-cl

Tracing 3D Anatomy in 2D Strokes: A Multi-Stage Projection Driven Approach to Cervical Spine Fracture Identification

arXiv:2601.15235v4 Announce Type: replace-cross Abstract: Cervical spine fractures require rapid and accurate diagnosis, yet automatic CT interpretation remains challenging as subtle injuries must be

Local Ai

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation

arXiv:2607.02798v1 Announce Type: new Abstract: Modern image-and-text-to-video diffusion models can synthesize highly realistic videos by iteratively denoising an initial Gaussian noise tensor conditi

local-aiarxiv-cs-cv

Trading Confidence: Comprehensive Uncertainty Estimation in Algorithmic Trading

arXiv:2607.02864v1 Announce Type: new Abstract: Reinforcement Learning (RL) has emerged as a powerful approach in financial trading, enabling agents to learn optimal strategies through direct market i

tutorialsarxiv-cs-lg

Train Smarter, Not Longer: Memorization-Guided Data Reuse for Efficient LLM Training

arXiv:2607.04969v1 Announce Type: cross Abstract: The training paradigm of large language models has shifted from traditional one-pass training to multi-epoch training, as reasonable reuse of limited

tutorialsarxiv-cs-cl

Training-Free Model Selection and Domain-Aware Score Calibration for First-Shot Anomalous Sound Detection

arXiv:2607.04526v1 Announce Type: cross Abstract: First-shot anomalous sound detection in DCASE Challenge Task 2 must flag anomalies of unseen machine types with a single threshold, without knowing wh