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Think Short, Defer Smart, Act, and Repeat: Calibrated Reasoning and Uncertainty-Aware Deferral for Edge LLM Agents

arXiv:2607.26865v1 Announce Type: cross Abstract: LLM agents following the ReAct paradigm are promising enablers of complex multi-step tasks, including multi-hop question answering, code generation, a

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TREA-Net: A Transferable Residual Epidemiological Adaptation Network for Dengue Incidence Forecasting

DGX agent

arXiv:2607.26854v1 Announce Type: new Abstract: Accurate multi-week dengue forecasting supports timely vector-control interventions, outbreak preparedness, and healthcare resource allocation. However,

local-aiarxiv-cs-lg

30 Jul 2026

Try Again, Don't Look Back: Blind Resampling Outperforms Self-Repair in Small Code Models

arXiv:2607.26117v1 Announce Type: cross Abstract: Self-repair - returning a failed program to the model together with its test output and asking for a correction - is a standard component of code agen

TurboVLA: Real-Time Vision-Language-Action Model at 32 Hz on an RTX 4090 with <1 GB VRAM

arXiv:2607.27205v1 Announce Type: new Abstract: Vision-language-action (VLA) models commonly adopt an LLM-centric V o L o A pathway, where visual observations are projected into the representation spa

Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation

arXiv:2607.26599v1 Announce Type: new Abstract: Estimating heterogeneous treatment effects is central to targeted interventions, such as personalized promotions and precision medicine. We focus on the

What actually happened to the whole Openclaw frenzy?

A while back you couldn't open reddit or youtube without sifting through tons of Openclaw content. And it wasn't just the internet that blew up, I remember seeing images from China where crowds would

Where Physics Meets Privacy: Federated PINNs for Privacy-Preserving Brain Tumor Biomechanical Modeling

arXiv:2607.26207v1 Announce Type: new Abstract: Brain tumors such as glioma, meningioma, and pituitary adenoma alter the mechanical behavior of soft brain tissue, yet common diagnostic methods rely on

3090 owners, what vram tempature do you get under ai load?

Hello Can you please share the tempature you get on your rtx 3090 under active llm load? Im trying to findout if my rtx 3090's tempatures are healthy or not please share VRAM Tempature only, you can t

A Control System, a Dataset, and a Recipe for Making Frozen LLM Agents Learn a Domain

arXiv:2607.25415v1 Announce Type: new Abstract: Production LLM agents are increasingly assembled from a frozen model wrapped in a harness: a prompt template, a tool set, a memory/retrieval layer, a pl

Amortising Trajectory Optimisation for Residual MPC via Implicit Contact Differentiation

arXiv:2607.24959v1 Announce Type: cross Abstract: Differentiable simulation can accelerate contact-rich trajectory optimisation by exposing local sensitivities of task outcomes to controls. Existing a

AMRD: Adaptive Multi-Teacher Relational Distillation for Lightweight Speech Emotion Recognition

arXiv:2607.25289v1 Announce Type: new Abstract: On-device speech emotion recognition (SER) is critical for real-time applications, yet large self-supervised models that excel at SER are too costly for

Beyond Counts: A Distributional Robustness Margin For Pathology Foundation Models

arXiv:2607.25497v1 Announce Type: cross Abstract: Pathology foundation models are approaching clinical deployment, yet remain vulnerable to systematic non-biological variation across centres. Differen

Beyond Zooming: Learning Multi-Tool Visual Reasoning for Ultra-High-Resolution Remote Sensing

arXiv:2607.25993v1 Announce Type: new Abstract: Ultra-high-resolution (UHR) remote-sensing (RS) imagery provides fine-grained Earth-observation evidence over city-scale scenes, but poses a fundamental

Bought a 5090 to escape API fees. Ended up building a mini datacenter. Sound familiar?

I bought an RTX 5090 last year just to run 27B models natively. I even fine-tuned it with my own data using LoRA, building RAGs and was pretty damn happy with the results at first. But, Q8 quantizatio

Comparing RAG and GraphRAG for Page-Level Retrieval Question Answering on a Math Textbook

arXiv:2509.16780v3 Announce Type: replace-cross Abstract: Large language models (LLMs) show promise as educational aids but often lack alignment with specific course materials. We investigate Retrieva

DC-WAM: Dynamic-Centric Visual Supervision and Reasoning for World-Action Models

arXiv:2607.25918v1 Announce Type: new Abstract: World-Action Models (WAMs) augment robot policies with future visual prediction, but it remains unclear what the visual modality should learn for contro

local-aiarxiv-cs-ro

Everyone posts day-one impressions. What's still in your stack a month later?

Day one threads are the least useful thing we produce here and we produce a lot of them. Model drops, forty people run their favourite prompt, half say it's the best thing ever and half say benchmaxxe

FlashEvaluator: Expanding Search Space with Parallel Sequence-Level Evaluation

arXiv:2603.02565v2 Announce Type: replace-cross Abstract: The Generator-Evaluator (G-E) framework generates K candidate sequences and uses an evaluator to select the highest-scoring one, which is wide

local-aiarxiv-cs-cl

GeoMFD: Continual Drone-View Geo-Localization with Geometry-Aware Adapter and Margin-Field Distillation

arXiv:2607.25788v1 Announce Type: new Abstract: Existing drone-view geo-localization (DVGL) methods are mainly developed under a static training paradigm, where models are optimized for fixed environm

HiFi-UMI: Learning Deployable Manipulation Policies from High-Fidelity UMI Data Alone

arXiv:2607.25895v1 Announce Type: cross Abstract: Learning deployable manipulation policies is bottlenecked by the scarcity of data that is both high-fidelity and scalable. Real-robot teleoperation is

How Do LLMs Read Bug Reports? An Empirical Study of Attention in LLMs for Automated Program Repair

arXiv:2607.25873v1 Announce Type: cross Abstract: Large Language Model (LLM)-based Automated Program Repair systems are advancing rapidly, yet their performance remains inconsistent. Even when provide

I2VShield: An Efficient Proactive Defense Framework against DiT-based Image-to-Video Models

arXiv:2607.25522v1 Announce Type: cross Abstract: The rapid advancement of video generation models has led to the increasing misuse of image-to-video (I2V) models. Although substantial progress has be

i'll say it plainly, hermes agent desktop is the best agentic app i've used, and i'm a little mad i didn't find it sooner. it auto see the m…

i'll say it plainly, hermes agent desktop is the best agentic app i've used, and i'm a little mad i didn't find it sooner. it auto see the models i'm serving, laguna s 2.1 sitting on my dgx spark and

local-ainous-research--x

Impressive paper! It's on one of the hardest tasks for coding agents today. Of course, I am talking about kernel optimization. Coding agents…

Impressive paper! It's on one of the hardest tasks for coding agents today. Of course, I am talking about kernel optimization. Coding agents are usually not so great at this. Reasons: Unfamiliar low-l

local-aidair-ai--x

INTACT: Isomorphic Intent-to-Action Learning for Search-Free World Models

arXiv:2607.26056v1 Announce Type: new Abstract: Forward latent world models predict how actions change a scene, but recover actions for a desired change only through expensive test-time search. We int

local-aiarxiv-cs-ro

Interpretable Column Annotation with LLM-Symbolized Decision Process Materialization

arXiv:2607.25228v1 Announce Type: new Abstract: Column annotation (CA), including column type annotation (CTA) and column property annotation (CPA), aims to identify the meanings of table columns and

local-aiarxiv-cs-cl

Linear-LLM-SCM: Benchmarking LLMs for Coefficient Elicitation in Linear-Gaussian Causal Models

arXiv:2602.10282v2 Announce Type: replace Abstract: Large language models (LLMs) have shown potential in identifying qualitative causal relations, but their ability to perform quantitative causal reas

MARS: Multi-Agent Re-ranking for Repeat-Order Food Delivery Recommendation

arXiv:2607.25420v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in recommender systems, but it is often unclear how much performance can be obtained from strong pr

Mind the Missing Split: Resolving Feature Heterogeneity in Swarm Learning with Random Forests

arXiv:2607.25538v1 Announce Type: new Abstract: Swarm Learning is a decentralized collaborative learning mechanism that allows multiple organizations to train a shared model without central coordinati

Mondrian: On-Device High-Performance Video Analytics with Compressive Packed Inference

arXiv:2403.07598v2 Announce Type: replace Abstract: In this paper, we present Mondrian, an edge system that enables high-performance object detection on high-resolution video streams. Many lightweight

Ollama going down the Copilot path?

What happened? I just asked GLM 5.2 one question, and in 3 minutes (one agent) it used up 15% of my 5 hour limit to produce a single answer. At this rate, I'll exhaust the entire 5 hour limit in just

local-air-ollama

OmniDelta: Skill-Driven Budget Allocation for Token Compression in OmniLLMs

arXiv:2607.25669v1 Announce Type: new Abstract: Emerging Omni-modal Large Language Models (OmniLLMs) enable unified understanding of text, audio, and video, but their long audio-video token sequences

Physics-Informed CNN-LSTM for Street-Scale Urban Flood Prediction: Reconciling Aggregate Accuracy and Street-Level Plausibility

arXiv:2607.25148v1 Announce Type: new Abstract: Deep learning surrogate models trained with mean-squared-error loss produce statistically accurate but physically unconstrained flood predictions: water

ProcAgent: An Agentic Framework for Procedural Task Guidance on Edge with Human-in-the-Loop

arXiv:2607.24770v1 Announce Type: new Abstract: Procedural tasks such as furniture assembly and home repair impose substantial cognitive demands because users must interpret instructions, track task p

Robust Unsupervised Network Intrusion Detection via Federated Learning with Selective Aggregation under Anomalous Sample Contamination

arXiv:2607.25439v1 Announce Type: cross Abstract: Network intrusion detection systems (NIDS) have become essential for Internet of Things (IoT) environments, as malware targeting IoT devices continues

SAM3D-Guided Object-Centric Representation Alignment for Vision-Language-Action Models

arXiv:2607.25912v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have shown strong potential for general robot manipulation, but most existing models rely on 2D visual-language ba

TaylorPODA: A Taylor Expansion-Based Method to Improve Post-Hoc Attributions for Opaque Models

arXiv:2507.10643v4 Announce Type: replace-cross Abstract: Post-hoc model-agnostic local attribution (LA) methods have been widely adopted to explain opaque AI models by quantifying feature-wise contri

The idea: on a CPU the decode speed depends on the active params per token, not the total. My objective is trying to run a 10B at 100tok/s on a mid level PC (No GPU).

On the CPU, batch 1 is memory bandwidth bound. But if token/s = bandwidth / (bytes_per_weight * active_weights_per_token) the total number of parameters doesnt slow down the generation speed. So build

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

Understanding Semantic IDs: From Item Representation to Item Selection in Generative Recommendation

arXiv:2607.24995v1 Announce Type: new Abstract: Semantic IDs (SIDs) are now a central component of generative recommendation. Current SID-based systems assign three roles to the same token sequence. S

Vendor-agnostic ML inference on production edge devices [R]

local-air-machinelearning

I work on PostSlate, a video editing tool, and this comes out of our own work. We run ML models on-device, face detection and embedding among other things, which means we can't assume anything about t

An Integrated Deep Learning and Statistical Framework for Whole-Network Gene--Environment Association with Leaf Vascular Architecture

arXiv:2607.22763v1 Announce Type: new Abstract: Leaf veins exhibit remarkable diversity in architecture and patterning, yet existing gene--environment association studies have primarily quantified lea

Anatomy of a Frontier Lab Agent Intrusion: A Technical Timeline of the July 2026 Incident

The first autonomous agent cyberattack is an unprecedented event that deserves unprecedented transparency. Today we're sharing everything we can: a full technical timeline, an interactive replay, and

Athena-Brain Technical Report: An Efficient Robot Brain for General Intelligence and Embodied Interaction

arXiv:2607.18985v2 Announce Type: replace Abstract: Large language models (LLMs) have demonstrated remarkable capabilities in language understanding, reasoning, and world knowledge. As embodied agents

Beyond Local Inspection: Global, Guideline-Grounded Evaluation of Post-hoc XAI Methods for ECG Classification

arXiv:2607.24035v1 Announce Type: cross Abstract: Explainable AI (XAI) is used to assess whether artificial intelligence models rely on meaningful patterns, yet explanations that appear plausible for

BoneAgeTW2: Automated Skeletal Maturation Assessment via the Tanner-Whitehouse 2 Method, Deep Learning, and Clinical Report Generation with Distribution Curves

arXiv:2607.23224v1 Announce Type: cross Abstract: We present BoneAgeTW2, the first fully open-source system to automate the complete Tanner-Whitehouse 2 (TW2) clinical protocol for skeletal maturity a

CADER: Confidence-Aware Dynamic Evidence Reasoning for Long-Video Understanding

arXiv:2607.24582v1 Announce Type: cross Abstract: Long-video understanding increasingly relies on large vision-language models and tool-augmented reasoning, but most systems apply the same inference p

Co-Harness: Co-Evolving Harnesses and Model Weights for LLM Agents

arXiv:2607.22688v1 Announce Type: new Abstract: Post-training agents for automated AI research requires optimizing not only model parameters, but also the runtime harness that shapes how research traj