Search: “context”

PUDA: An AI-Native Hardware Harness for Self-Driving Laboratories

arXiv:2607.26464v1 Announce Type: cross Abstract: Physical Unified Device Architecture (PUDA) is an AI-native hardware harness for self-driving laboratories (SDLs). Rather than building a human-center

agentsarxiv-cs-ai

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QuantWAMs: Calibrating at the Right Granularity for World Action Models

DGX agent

arXiv:2607.28405v1 Announce Type: cross Abstract: World Action Models (WAMs) jointly predict future observations and actions, but their iterative denoising and closed-loop execution make efficient dep

researcharxiv-cs-lg

31 Jul 2026

Revisiting Predictive Process Monitoring in the Age of Foundation Models: A Comparative Study of Sequence, Tabular, and LLM Approaches

arXiv:2607.27797v1 Announce Type: new Abstract: Predictive process monitoring (PPM) leverages event logs to forecast the future of running process instances, for instance, predicting the next activity

S-CEReBrO: Breaking the Memory Barrier in Continuous EEG Monitoring

arXiv:2607.27913v1 Announce Type: new Abstract: Foundation models offer a promising paradigm for Electroencephalography (EEG) analysis, leveraging generalizable representations from vast unlabeled dat

SARC-DQ: Runtime Data-Quality Gating for Agentic AI: Silent Evidence Defects, the Incompetence Shield, and Downstream-Only Remediation

model-releasesarxiv-cs-ai

arXiv:2607.26313v1 Announce Type: cross Abstract: Agentic systems act, so a defect in the evidence they retrieve becomes a wrong action with a currency cost. The most dangerous enterprise defects are

ScaFE: Data-Efficient Scar Classification with LLM-Generated Clinical Feature Programs

arXiv:2607.28538v1 Announce Type: new Abstract: Classifying pathological scars from clinical photographs requires distinguishing keloids from hypertrophic scars despite limited expert-labeled data and

local-aiarxiv-cs-cv

Scaling Vision-Language Models Is Not Enough to Mitigate Bias

model-releasesarxiv-cs-cv

arXiv:2607.28211v1 Announce Type: new Abstract: Vision-Language Models (VLMs) such as CLIP are now foundational to multimodal systems, yet their robustness to spurious correlations remains poorly unde

Semantic-Aligned Structural Abstraction for Multimodal Sentiment Analysis

arXiv:2607.27790v1 Announce Type: new Abstract: Multimodal Sentiment Analysis (MSA) aims to interpret complex human emotions by integrating natural language with non-verbal modalities. Non-verbal moda

Stage-Replay Divergence Follows the KV Cache: Fixed-Prefix Precision Controls and Bidirectional Cache Transplantation

arXiv:2607.28495v1 Announce Type: cross Abstract: Stage-replay diagnostics reconstruct intermediate token prefixes and treat fresh-prefill continuation as continuation from the decoder state that orig

State-Dependent Safety Failures in Multi-Turn Language Model Interaction

arXiv:2603.15684v2 Announce Type: replace-cross Abstract: Safety alignment in large language models is typically evaluated under isolated queries, yet real-world use is inherently multi-turn. Although

safetyarxiv-cs-ai

Subtract or Replay? Exact Deletion from Language-Model Memory

model-releasesarxiv-cs-cl

arXiv:2607.27539v1 Announce Type: cross Abstract: Exact deletion from persistent language-model memory depends on how that memory represents a record. Addressable influence can be removed by algebraic

TacWAM: Anchor-Guided World Action Model with Mechanics-Aware Tactile Prediction

arXiv:2607.28391v1 Announce Type: new Abstract: World Action Models (WAMs) combine future-state prediction with robot action generation, but existing approaches largely rely on visual futures. Visual

applicationsarxiv-cs-ro

Thinking Once Is Enough: Intermediate-Layer Evidence Routing for High-Resolution VQA

model-releasesarxiv-cs-cv

arXiv:2607.27830v1 Announce Type: new Abstract: High-resolution visual question answering (HR-VQA) is often treated as a problem of insufficient evidence acquisition, where failing multimodal large la

ThreatForest: Multi-Agent Attack Tree Generation with Pluggable TTP Framework Mapping

arXiv:2607.27528v1 Announce Type: cross Abstract: Threat modeling is essential for secure software development, yet manual analysis of cloud-native architectures is slow and demands scarce security ex

agentsarxiv-cs-cl

VCP-DCN: Beyond Visual Concealed Property via Depth Collaborative Network for Camouflaged Object Detection

arXiv:2607.27843v1 Announce Type: new Abstract: Camouflaged Object Detection (COD) aims to identify and segment camouflaged objects in complex environments, which are often concealed because their col

local-aiarxiv-cs-cv

VESTIGE: A Knowledge-Guided Masking Strategy for Corruption-Aware Fine-Tuning of Genomic Transformers, Validated on Ancient DNA Reconstruction

arXiv:2607.27712v1 Announce Type: new Abstract: Standard masked-language-model fine-tuning applies a uniform masking probability across every token position, assuming reconstruction difficulty is posi

ViewMind3D: Modular View-Aware Inference for Training-Free 3D-QA

arXiv:2607.28442v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) and vision-language models (VLMs) have enabled new possibilities for 3D question answering (3D-QA), a ke

applicationsarxiv-cs-cv

VisualRouter: Query-Grounded Visual Sampling for Long Video Understanding

arXiv:2607.28463v1 Announce Type: new Abstract: Large vision-language models (LVLMs) have achieved significant progress in video understanding, yet understanding long videos remains challenging due to

researcharxiv-cs-cv

What’s new in AI infrastructure and orchestration this month

model-releasesgoogle-cloud-ai

At Google, AI is a soup-to-nuts endeavor. Obviously, we make leading AI models like Gemini and Nano Banana. We incorporate AI into the tools you use every day (think Gmail, BigQuery, AlloyDB, Google C

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

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

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.

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

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

An Informativeness-based Clustered Federated Learning Method for Reliable Traffic Prediction in Managed Wi-Fi Networks

arXiv:2607.26682v1 Announce Type: cross Abstract: Centrally-managed Wi-Fi solutions are increasingly leveraging Distributed Artificial Intelligence (AI) to predict key operational statistics of Access

Contrastive ESA: Human Evaluation of Multiple Translations at Once

arXiv:2607.26640v1 Announce Type: new Abstract: Current human evaluation of machine translation typically assesses single outputs in isolation, a paradigm that suffers from high annotator noise and co

Deep Expert Injection for Anchoring Retinal VLMs with Domain-Specific Knowledge

arXiv:2603.07131v4 Announce Type: replace Abstract: Large Vision Language Models (LVLMs) show immense potential for automated ophthalmic diagnosis. However, their clinical deployment is severely hinde

researcharxiv-cs-cv

Dense Local Dependencies Induce Attention-Logit Explosion and Training Instability During Long-Sequence Transformer Training

arXiv:2505.15548v2 Announce Type: replace Abstract: Autoregressive transformer language models frequently exhibit training instability when trained on long sequences, particularly under low-precision

Differentially Private Permutation Tests

arXiv:2310.19043v3 Announce Type: replace-cross Abstract: Recent years have witnessed growing concerns about the privacy of sensitive data. In response to these concerns, differential privacy has emer

applicationsarxiv-cs-lg

Domain adaptation for handwriting trajectory reconstruction from IMU sensors

arXiv:2607.26736v1 Announce Type: new Abstract: Digital pens are commonly used to write on digital devices, providing the handwriting trace and enhancing human-computer interation. This study focuses

DuplexGen: Adaptive Synthesis of Human-AI Turn-Taking Dialogues

arXiv:2607.26178v1 Announce Type: new Abstract: Turn-taking is a central component of full-duplex interaction. Which turn-taking behaviors are appropriate varies with the scenario, yet current models

Embodied Agents Take Control: Minimal-Interface Zero-Shot Agents Rival Industrial-Scale Policies in Vision-and-Language Navigation

arXiv:2607.26148v1 Announce Type: new Abstract: Autonomous embodied agents must sustain a long decision-making loop that involves perceiving, acting, verifying, and self-correcting over many steps. Cu

agentsarxiv-cs-ro

Forecasting Trajectory-Level Safety Risks in Black-Box Multi-Turn Interactions

arXiv:2607.26820v1 Announce Type: new Abstract: As large language models (LLMs) evolve from standalone assistants into autonomous agents, ensuring their safety requires shifting beyond pointwise risk

safetyarxiv-cs-lg

From Tokens to Watt-hours: Analytical Energy Estimation for LLM Inference on Modern GPUs

arXiv:2607.26571v1 Announce Type: new Abstract: The operational energy consumption of large language model (LLM) inference is becoming an increasingly important component of the environmental footprin

HoF-Bench: Rediscovering Real AI-Discovered CVEs Without Frontier Models

arXiv:2607.27030v1 Announce Type: cross Abstract: LLM-based analyzers have begun finding real vulnerabilities in mature open-source projects: AISLE's analyzer is credited with more than 280 CVEs acros

How Kimi K3 Engineered Its Way to the Frontier [R]

model-releasesr-machinelearning

Kimi K3 by Moonshot reached the frontier as an open-weight model. Artificial Analysis ranks it fourth of 580 models, behind only Claude Opus 5, Fable 5, and GPT-5.6 Sol. Moonshot released more than th

Identifying Implicit Bias in LLM-based Chat AI Toward People with Intellectual Disabilities

model-releasesarxiv-cs-cl

arXiv:2607.26062v1 Announce Type: cross Abstract: Background: This work investigates the presence of implicit bias in Large Language Model (LLM)-based chat AI models directed toward people with intell

Interesting data from the OpenRouter Kimi K3 dashboard: @togethercompute offers one of the lowest prices for @Kimi_Moonshot K3 while also ac…

Interesting data from the OpenRouter Kimi K3 dashboard: @togethercompute offers one of the lowest prices for @Kimi_Moonshot K3 while also achieving one of the highest prompt cache hit rates. Low prici

agentstogether-ai--x

Introducing the Parse Gateway There's been an explosion of interest in model routing - you don't always need the best model for every task. …

Introducing the Parse Gateway There's been an explosion of interest in model routing - you don't always need the best model for every task. That is especially true for document parsing 📄🔀: - Some page

agentsjerry-liu--x

Investigating reservoir computing for branch predictionin pipelined processors using emerging CMOS memristor devices

arXiv:2607.27140v1 Announce Type: cross Abstract: This project aimed to develop a novel reservoir compute (RC) implementation framework targeting high-speed operation and integration with CMOS digital

JEPADepth: Masked Predictive Representation Learning for Self-Supervised Monocular Depth Estimation

model-releasesarxiv-cs-cv

arXiv:2607.26600v1 Announce Type: new Abstract: Self-supervised monocular depth estimation typically relies on photometric reconstruction losses that couple depth, pose, and appearance assumptions. In

Just for reference, from what I observed in my Using Local Coding Agents blog article last month: https://x.com/rasbt/status/207051816739969…

model-releasessebastian-raschka--x

Just for reference, from what I observed in my Using Local Coding Agents blog article last month: https://x.com/rasbt/status/2070518167399698490?s=20 'I tried to analyze why Claude Code uses more toke

Keyless Attention: Value-Space Routing and Value-Only Caching for Efficient Transformers

arXiv:2606.21848v2 Announce Type: replace Abstract: Transformer architectures form the foundation of modern natural language processing, making it crucial to address the efficiency and scalability lim

Large Emotional World Model

arXiv:2512.24149v2 Announce Type: replace Abstract: The world is governed by both physical laws and affective dynamics. Physical laws govern state transitions, while affective dynamics shape human act

Latent-IM: Latent Interaction Management for Speech LLMs

arXiv:2607.26928v1 Announce Type: new Abstract: Classical spoken dialogue systems often separated dialogue management from response realization: a policy selected the next dialogue action, and a gener

safetyarxiv-cs-cl

LG AI Research releases K-EXAONE 2.0 750B A37B

model-releasesr-localllama

It was developed under Phase 2 of Korea's Sovereign AI Foundation Model Project. Size: 750B parameters (3x larger than their 236B v1 model). - License: Apache 2.0 Languages: Expanded to 10 language

LLMET: Enabling Cross-Layer Evaluation of Emerging M3D Memories for Energy-Efficient LLM Serving

arXiv:2607.26491v1 Announce Type: cross Abstract: The energy consumption of Large Language Model (LLM) serving is becoming a major system challenge as deployment scales, driven by hardware power and t

MedARC: Training-Free Adaptive Redundancy Compression of Visual Tokens for 3D Medical Vision-Language Models

arXiv:2607.26554v1 Announce Type: new Abstract: Integrating 3D medical images with vision-language models (VLMs) holds substantial promise for computer-aided diagnosis. However, volumetric images gene

local-aiarxiv-cs-cv