All entries

Where and When to Commit: Candidate-Aware Decoding for Diffusion Language Models

arXiv:2607.28166v1 Announce Type: new Abstract: Diffusion language models (DLMs) expose a provisional prediction at every denoising step, creating an opportunity for generation-time early exit that st

researcharxiv-cs-cl

WhisperRec: Latent Reasoning for Efficient Foundation Recommendation Models

DGX agent

arXiv:2607.26621v2 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated strong reasoning capabilities, motivating their adoption as backbones for foundation recommendation mod

model-releasesarxiv-cs-ai

31 Jul 2026

Why are AI model tests always the same generic prompts?

model-releasesr-localllama

Okay, hear me out. Why is it that every time a new model comes out, all the tests I see are 'make a car game,' 'make a website,' or something equally generic, usually from a prompt that's barely a lin

Why Are GUI Agents Correct but Late? Decode on the Decision-Time Critical Path, Tested with Pre-Compiled Policy Trees

model-releasesarxiv-cs-lg

arXiv:2607.28399v1 Announce Type: new Abstract: Computer-use agents often fail on transient GUI events because they produce the correct action only after the relevant window has already closed. We ide

WIDE: Boosting Adaptive LLM Inference via Token-level Dynamic Width Pruning

arXiv:2607.28418v1 Announce Type: cross Abstract: Pruning is a promising approach for improving the efficiency of LLMs. Existing static structured pruning methods are hardware-friendly and can deliver

applicationsarxiv-cs-cl

Will ollama upgrade Deepseek V4 Flash on cloud?

https://preview.redd.it/vxl4zslewigh1.png?width=1435&format=png&auto=webp&s=5a419870ca0cb13076be6c9ff4ef33d8177d5eda New version is 25% better than previous one and is near GLM-5.2 quality submitted b

model-releasesr-ollama

Windowed thinning and query complexity for the bouncy particle and Zigzag samplers

arXiv:2607.28413v1 Announce Type: cross Abstract: Let mu(d x)propto e^{-U(x)} d x on R^d, where U is m-strongly convex and L-smooth, and denote by kappa=L/m the condition number. We consider windowed

Wiring diagram extraction and gluing: a case study in classifying figure skating jumps using 3D dataset

arXiv:2607.27598v1 Announce Type: cross Abstract: Hasse clustering is an algorithm that extracts common patterns in sequential data and represents them in graphical forms. As the number of expected cl

applicationsarxiv-cs-lg

With release of Deepseek V4 I wanted see how the model sizes are trending over time. The trend is that by this time next year, we probably will have Opus 4.5 level models on consumer grade laptops!

model-releasesr-localllama

I was surprised to see that Deepseek V4 Flash is extremely smart and small enough to fit in setup that can be built with < $50,000. Expensive, but not a datacenter. So I wanted to see the trend over t

Witness Evidence Portfolios: Single-Prefill Risk Detection for Closed Multimodal Answers

arXiv:2607.27667v1 Announce Type: new Abstract: Reliable deployment of multimodal large language models (MLLMs) requires deciding whether a confident visual answer should be trusted, reviewed, or rout

World Action Planner: Generalizable Decision-Making with Action-Conditioned World Models

arXiv:2607.27599v1 Announce Type: cross Abstract: Building generalizable agents for diverse applications remains a fundamental challenge. While imitation learning-based policies succeed in specific tr

safetyarxiv-cs-ro

Would You Walk to the Car Wash? Revealing the Salience Bias of Large Language Models in Commonsense Reasoning

model-releasesarxiv-cs-cl

arXiv:2607.28478v1 Announce Type: new Abstract: As large language models (LLMs) continue to advance in complex reasoning tasks, they have learned to heavily prioritize explicit conditions provided in

Write-Safe Flow Field Mapping under Ambiguous Onboard Sensing and Localization Drift

arXiv:2607.27713v1 Announce Type: new Abstract: Mobile robots can infer local flow structure from onboard sensing, but a locally plausible estimate is not always safe to write into a global map. Simil

local-aiarxiv-cs-ro

X-NavDP: Generalizing Navigation Diffusion Policy to Novel Behavior and Embodiments with Group Q-score Reweighted Matching

arXiv:2607.28560v1 Announce Type: new Abstract: Pretraining navigation diffusion policies rely on large-scale expert demonstrations. These data are typically generated by a fully-informed oracle plann

local-aiarxiv-cs-ro

You Only Look Omni Gradient Backpropagation for Moving Infrared Small Target Detection

arXiv:2511.13013v2 Announce Type: replace Abstract: Moving infrared small target detection is a key component of infrared search and tracking systems, yet it remains extremely challenging due to low s

ZAPs: A Reward Attribution Framework for DeFi Ecosystems with Adversarial-Robust Scoring via Parallel Anomaly Ensemble Detection

arXiv:2607.27859v1 Announce Type: cross Abstract: Incentive programs are central to user acquisition in decentralized finance, but many reward systems rely on raw volume, transaction count, and wallet

applicationsarxiv-cs-lg

Zero-Shot Face-to-Speech Synthesis via Latent Space Adaptation of a Style-Diffusion TTS Model

arXiv:2607.26742v1 Announce Type: cross Abstract: Zero-shot text-to-speech (TTS) clones a voice from a short audio prompt, but this reliance on reference audio is a barrier when only visual informatio

researcharxiv-cs-ai

ZMIS-SAM: Segment Anything Model Enhanced with Wavelet Transform for Zooplankton Microscopy Image Instance Segmentation

arXiv:2607.27585v1 Announce Type: new Abstract: As primary consumers in the marine food chain, zooplankton play a crucial role in maintaining marine ecological balance. However, the Segment Anything M

ZUNA1.1: A more flexible EEG foundation model for Denoising and Super-resolution

model-releasesarxiv-cs-lg

arXiv:2607.27308v1 Announce Type: new Abstract: We introduce ZUNA1.1, a 380M-parameter diffusion autoencoder for flexible EEG signal reconstruction. ZUNA1.1 is capable of reconstructing variable lengt

2 images + 1 prompt > expected output

Hi, I'm trying to replicate a thing locally, that I can do on ChatGPT. What I want is to give a local AI two reference images (a face and a background item) and a prompt about the composition of the p

local-air-ollama

2× Radeon R9700 for Local AI Was Choosing AMD Instead of NVIDIA a Mistake Without CUDA?

Hello together I decided to go with 2× Radeon AI PRO R9700 GPUs (64 GB total VRAM) for my local AI server. However, I keep reading that AMD/ROCm is still not as mature as NVIDIA/CUDA when it comes to

local-air-localllama

3DGBGS: 3D Granular Ball Gaussian Splatting for Compact Novel View Synthesis

arXiv:2607.26578v1 Announce Type: new Abstract: Three-dimensional Gaussian Splatting (3DGS) enables high-quality real-time novel-view synthesis through explicit Gaussian primitives and differentiable

local-aiarxiv-cs-cv

4090 + 5060 Ti + 64GB RAM: 206 t/s on a 35B-A3B, and a 122B at 37 t/s

model-releasesr-localllama

I've been benchmarking a two-card box for a few weeks and I still can't quite get over some of these numbers, so I'm dumping them here. Box: RTX 4090 (24GB) + RTX 5060 Ti (16GB), i9-13900K, 64GB DDR5.

A Closer Look at Dynamic Scene Graph Generation In the Era of Multimodal Large Language Models

arXiv:2503.15846v2 Announce Type: replace Abstract: Dynamic Scene Graph Generation (DSGG) aims to capture objects and their evolving relations in videos. Despite recent progress, the practicality and

A Compositional Theory of Causally Masked Transformers

arXiv:2607.26988v1 Announce Type: cross Abstract: What types of decision problems can a causally masked, finite-precision transformer solve for inputs of arbitrary length? Existing answers often rely

A fundamental flaw leaves LLMs strikingly vulnerable to attack

It is impossible to make large language models fully secure against hacks because of a fundamental flaw in how they work, a team of researchers argue in a paper presented at the International Conferen

safetymit-tech-review

A large-scale corpus of religious radio broadcast transcripts from webstream recordings in the United States

arXiv:2607.26249v1 Announce Type: new Abstract: Religious radio is a widespread but understudied form of mass communication in the United States, and content-level analysis of it has been constrained

researcharxiv-cs-cl

A Persona-based Rate Action Index

arXiv:2607.26545v1 Announce Type: cross Abstract: We propose an index for predicting the U.S. Federal Open Market Committee (FOMC) decision to hike/hold/cut the current federal funds target rate based

safetyarxiv-cs-lg

A Picture Says Thousands of Words - Harnessing Dermal Exposure Data from Images through Hybrid Deep Learning for Enhanced Safety Assessment

arXiv:2607.26170v1 Announce Type: new Abstract: This study developed a hybrid computer vision method to quantify exposed skin from images for dermal exposure assessment. Using 170 indoor-painting imag

safetyarxiv-cs-cv

Agents

A post of ours on vendor lock in and LLMs. We don't like the growing trend of AI companies quietly hiding your data while stripping away you…

A post of ours on vendor lock in and LLMs. We don't like the growing trend of AI companies quietly hiding your data while stripping away your control. We think that's bad for users and bad for the eco

agentsharrison-chase--x

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

ActSWM: Action-Sensitive World Models for Long-Horizon Planning in Open-World Games

arXiv:2607.26712v1 Announce Type: new Abstract: Latent world models support efficient model-predictive control by optimizing future control sequences in latent space and replanning in a receding-horiz

local-aiarxiv-cs-ro

AdaMARP: An Adaptive Multi-Agent Interaction Framework for General Immersive Role-Playing

model-releasesarxiv-cs-cl

arXiv:2601.11007v2 Announce Type: replace-cross Abstract: LLM role-playing aims to portray arbitrary characters in interactive narratives, yet existing systems often suffer from limited immersion and

Adaptive Gradient-Based Methods for a Broader Class of Optimization Problems under Performative Prediction

arXiv:2607.26562v1 Announce Type: cross Abstract: We study optimization under performative prediction, where deploying a model affects the future data distribution. For this setting, several gradient-

Adaptively Robust LLM Monitoring via Activation Watermarking

arXiv:2603.23171v3 Announce Type: replace-cross Abstract: Providers monitor deployed large language models (LLMs) to detect misuse that they cannot prevent. LLM monitoring is deterministic and often o

local-aiarxiv-cs-lg

Advancing the price-performance frontier with GPT‑5.6

model-releasessimon-willison

Advancing the price-performance frontier with GPT‑5.6 Huge price drop from OpenAI today: GPT-5.6 Terra got a 20% reduction, and GPT-5.6 Luna got a massive 80% drop. OpenAI credit 5.6 Sol with enabling

AgentGFM: A Graph Foundation Model with Node-Agent Information-Flow Control

arXiv:2607.26533v1 Announce Type: new Abstract: Graph Foundation Models (GFMs) aim to learn transferable knowledge from multi-domain graphs and adapt to unseen scenarios. As a fundamental source of re

safetyarxiv-cs-lg

AgentGUI: An Interface for Observing and Steering Long-Running AI Agents

arXiv:2607.26300v1 Announce Type: new Abstract: AI agents are increasingly adept at tackling complex, long-running tasks. With the rapid surge of autonomous capabilities, human oversight is systematic

local-aiarxiv-cs-cl

AgentSnare: Learning to Delay, Divert, and Defuse Autonomous Penetration Agents

arXiv:2607.26998v1 Announce Type: cross Abstract: Large language model (LLM) agents automate penetration testing through an observation-action loop, selecting actions based on observations returned by

safetyarxiv-cs-cl

AI Alignment in Medical Imaging: Unveiling Hidden Biases Through Counterfactual Analysis

arXiv:2504.19621v2 Announce Type: replace Abstract: Machine learning (ML) systems for medical imaging have demonstrated remarkable diagnostic capabilities, but their susceptibility to biases poses sig

safetyarxiv-cs-lg

Agents

AI engineers are rediscovering ontologies as a way to keep probabilistic agents inside deterministic boundaries. We delve into presentations…

AI engineers are rediscovering ontologies as a way to keep probabilistic agents inside deterministic boundaries. We delve into presentations from @coyle_frankp and @emileifrem from the @aiDotEngineer

agentsswyx--x

“AI Meltdown” is the scenario where the agent goes off the rails and forgets/ignores all previous instructions and soft guardrails. No promp…

model-releasesperplexity--x

“AI Meltdown” is the scenario where the agent goes off the rails and forgets/ignores all previous instructions and soft guardrails. No prompt injection or malicious actor is needed for this to happen.

AIGen: Automating AI Bill of Materials Generation Through Hybrid MLOps Integration

arXiv:2607.26652v1 Announce Type: new Abstract: The responsible development and deployment of artificial intelligence (AI) systems requires rigorous documentation of their constituent artifacts, e.g.,

Aligning LLM-Simulated and Human Examinees for Psychometric Calibration: A Cognitive Diagnostic Profiling Approach

model-releasesarxiv-cs-cl

arXiv:2607.26317v1 Announce Type: cross Abstract: Psychometric calibration for educational tests typically requires costly human response data. Large language models (LLMs) simulated examinees offer a

AlloyDB adds group authentication to secure enterprise scale and AI agents

Database security traditionally relies on a fragile balance between the granular control developers need and the administrative overhead of managing thousands of individual database passwords. Between

safetygoogle-cloud-ai

Industry

Amazon’s stock pops on roaring cloud growth and soaring AI demand

Amazon.com Inc. delivered a solid earnings and revenue beat as it posted its second-quarter financial results, driven by surging growth in its cloud infrastructure business. Demand for artificial inte

industrysiliconangle

Amortized Moment Matching for Visual Generation

model-releasesarxiv-cs-lg

arXiv:2607.26860v1 Announce Type: new Abstract: We propose amortized moment matching, utilizing neural networks to learn data moments as distributional training signals. By casting diffusion denoisers

An Attention-Based Framework for Alzheimers Disease Classification Using Resting-State fMRI

arXiv:2607.26746v1 Announce Type: cross Abstract: Accurate identification of Alzheimers disease (AD) using resting-state functional magnetic resonance imaging (rs-fMRI) remains challenging due to the