Search: “models”

MNIST-PRO: MNIST is Back as a Partially Observable World for AI Agents

arXiv:2608.31022v1 Announce Type: new Abstract: AI agents in partially observable environments need to coordinate active sensing with working memory to maintain an evolving perceptual state. However,

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N_0-Foundation: Towards the Age of Tactile Intelligence

DGX agent

arXiv:2608.29601v1 Announce Type: cross Abstract: We present N_0-Foundation, a paradigm for tactile-enabled embodied manipulation, which integrates tactile sensing hardware, large-scale multimodal dat

model-releasesarxiv-cs-cv

1 Sept 2026

Over the summer, we have been sprinting on safety priorities; it's more important than ever for capabilities and safeguards to advance toget…

model-releasessam-altman--x

Over the summer, we have been sprinting on safety priorities; it's more important than ever for capabilities and safeguards to advance together. We have more to do but have made a lot of progress. We

Personas Differ from Native-Language Generation: Language Pathways Shape LLM Interpersonal Advice

arXiv:2608.30873v1 Announce Type: cross Abstract: LLMs are increasingly used for interpersonal advice and as tools for studying social behavior across languages and cultures. A common shortcut for eli

researcharxiv-cs-ai

Polis: 3D Self-Supervision at City Scale

arXiv:2608.29426v1 Announce Type: cross Abstract: Reliable semantic representations derived from city-scale 3D models are increasingly important for urban analysis, infrastructure monitoring, autonomo

post-graph-rag: A PostgreSQL-Native Bi-Temporal Graph RAG Engine with Temporal Grounding at Synthesis

arXiv:2608.24921v2 Announce Type: replace Abstract: Graph RAG connects facts no single passage states, but implementations pay three times: in infrastructure, keeping vector store, graph database and

QAQ: Bidirectional Semantic Coherence for Selecting High-Quality Synthetic Code Instructions

arXiv:2603.12165v3 Announce Type: replace Abstract: Synthetic data has become essential for training code generation models, yet it introduces significant noise and hallucinations that are difficult t

Randomized YaRN Improves Length Generalization for Long-Context Reasoning

arXiv:2606.23687v2 Announce Type: replace Abstract: Large language models (LLMs) are typically pretrained on short sequences and then extended to work on longer sequences with additional training. How

ReGraP-LLaVA: Reasoning enabled Graph-based Personalized Large Language and Vision Assistant

arXiv:2505.03654v3 Announce Type: replace-cross Abstract: Multimodal Large Language Models have shown strong performance across multimodal tasks, and recent personalized MLLMs can recognize user-speci

Retrieval-Augmented LLM Agents: Learning to Learn from Experience

arXiv:2603.18272v2 Announce Type: replace Abstract: While large language models (LLMs) have advanced the development of general-purpose agents, robust generalization to unseen tasks remains challengin

Self-Supervised Pretext Tasks for Infant Cry Analysis: A Controlled Comparison and a Cautionary Result on Donateacry

arXiv:2608.30456v1 Announce Type: new Abstract: We compare six self-supervised pretext tasks for infant cry analysis under a fixed budget, meaning the same compact encoder of 1.17M parameters, the sam

SERA-H: Super-Resolution of Sentinel Time Series for Fine-Scale Canopy Height Mapping

arXiv:2512.18128v4 Announce Type: replace Abstract: High-resolution mapping of canopy height is essential for forest management and biodiversity monitoring. Although recent studies have led to the adv

SHAPE of Chain-of-Thought in Math Reasoning

arXiv:2608.28600v1 Announce Type: new Abstract: Large language models (LLMs) achieve strong performance on mathematical reasoning benchmarks, yet the mathematically meaningful skills underlying their

applicationsarxiv-cs-ai

SIR: Self-improving Red-teaming for Compute Use Agents

arXiv:2608.30207v1 Announce Type: cross Abstract: Computer use agents (CUAs) are vision-language models that perceive a screen and act on a real operating system through mouse, keyboard, and terminal,

SkillRet: A Large-Scale Benchmark for Skill Retrieval in LLM Agents

arXiv:2605.05726v2 Announce Type: replace Abstract: As LLM agents are increasingly deployed with large libraries of reusable skills, selecting the right skill for a user request has become a critical

SpecPV: Improving Self-Speculative Decoding for Long-Context Generation via Partial Verification

arXiv:2512.02337v2 Announce Type: replace Abstract: Growing demands from tasks like code generation, deep reasoning, and long-document understanding have made long-context generation a crucial capabil

Safety

Stratified Consistency Distillation for Natural Language Formalization

arXiv:2608.30258v1 Announce Type: cross Abstract: Neurosymbolic reasoning has shown promising success in addressing complex reasoning tasks by combining large language models (LLMs) and symbolic solve

safetyarxiv-cs-ai

The Differential Reasoning Router: Operationalizing Cost-Aware LLM Annotation in E-commerce

arXiv:2608.30224v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used to annotate structured product data in e-commerce, but early deployment often begins as a cold-star

applicationsarxiv-cs-ai

The Double-Edged Nature of the Rashomon Set for Trustworthy Machine Learning

arXiv:2511.21799v2 Announce Type: replace Abstract: Real-world machine learning (ML) pipelines rarely produce a single model; instead, they produce a Rashomon set of many near-optimal ones. We show th

applicationsarxiv-cs-lg

The Price of Intelligence: A Quality-Adjusted Price Index for AI Services

arXiv:2608.29843v1 Announce Type: cross Abstract: Posted prices for AI inference have fallen steadily since 2024, yet the measured speed of that fall depends almost entirely on the method of measureme

Token-Efficient Data Reasoning Agents via Adaptive Structuring of Unstructured Data

arXiv:2608.31082v1 Announce Type: new Abstract: Valuable data remains embedded in unstructured sources: web pages, reports, contracts, filings, earnings calls, and PDFs. The big bet in enterprise AI i

Towards a Joint Khmer Text Recognition and Word Segmentation

arXiv:2608.30213v1 Announce Type: cross Abstract: Text recognition, or extracting electronic text from document images, has been indispensable for knowledge retrieval tasks, such as retrieval-augmente

ToxLens: A Reproducible Graph-Learning Framework for Leakage-Aware, Uncertainty-Calibrated Molecular Toxicity Prediction

arXiv:2608.30472v1 Announce Type: new Abstract: Molecular toxicity prediction is increasingly used to prioritise compounds before experimental testing, but conventional benchmark performance can overs

WeAgent-MMSearch: Native Text-Vision Interaction for Multimodal Search Agents

arXiv:2608.28062v2 Announce Type: replace Abstract: Multimodal search agents extend parametric knowledge with newly emerging and long-tail evidence from the open web. Yet many existing agentic search

Weaving Visual Narratives: Agentic Image Bundle Composition Beyond Atomic Visual Matching

arXiv:2608.28695v1 Announce Type: new Abstract: Image retrieval has traditionally been formulated as a point-wise matching problem, where each candidate image is scored in isolation. However, this ato

Safety

When Safety Speaks a Language: A Mechanistic Analysis of Safety-Language Identity Entanglement in LLMs

arXiv:2608.29936v1 Announce Type: new Abstract: Safety alignment of large language models (LLMs) degrades across languages, yet the internal mechanism driving this asymmetry remains poorly understood.

safetyarxiv-cs-cl

When to Adapt: Conditional Memory Adapters for Retention-Preserving Domain Specialization

arXiv:2608.29327v1 Announce Type: new Abstract: Large language models deployed in specialized domains must improve in-domain performance without sacrificing general capabilities. Existing parameter-ef

Wrong Prediction, Right Answer: Recovering Evidence from Collapsed LLM Sequence Scores

arXiv:2608.31068v1 Announce Type: new Abstract: When a large language model fails a reasoning task, it is often assumed to lack the underlying capability. However, this conflates a genuine absence of

Abstract4D: A Large-Scale Dataset and Framework for Understanding the Visual Language of Abstract Art

arXiv:2608.28339v1 Announce Type: new Abstract: Artificial intelligence can classify artistic styles and synthesize images, but it still lacks a model of the visual language that gives art meaning. Ab

Accelerating LLM Inference via Vector Index Based Output Embeddings

arXiv:2608.27460v1 Announce Type: new Abstract: Large output embedding matrices create a significant memory bandwidth bottleneck during autoregressive decoding, especially for compact LLMs with large

b10726

model-releasesllama-cpp-releases

AVX2: Speed up large batch size prompt processing of IQ models (#27402) Batched gemm for grid IQ quants Style updates and a bit more performance Clean up comments Move code around Vectorize IQ panel d

Beyond Non-IID: Learner--Client Distribution Mismatch in Federated Learning

arXiv:2608.27715v1 Announce Type: new Abstract: Federated learning systems are increasingly deployed to facilitate collaborative model training across a heterogeneous client population. Existing pract

local-aiarxiv-cs-lg

CoCoBench: A Cooperative Coordination Benchmark for Embodied Multi-Agent Task Planning

model-releasesarxiv-cs-ro

arXiv:2608.28266v1 Announce Type: new Abstract: Agent systems powered by multimodal large language models (MLLMs) have advanced rapidly in recent years, yet existing embodied-agent benchmarks still la

Cyc3D: Evaluating Cyclic Structural Stability and Asset Usability in Image-to-3D Generation

arXiv:2608.28080v1 Announce Type: new Abstract: Image-conditioned 3D generation has advanced rapidly, yet existing evaluation protocols largely judge rendered-view plausibility and semantic alignment,

Destroy Me: Automatic Artifact Generation for Histopathology Images

arXiv:2608.27516v1 Announce Type: cross Abstract: Deep learning's diagnostic utility in pathology is constrained by model vulnerability to real-world data imperfections. While current strategies favor

applicationsarxiv-cs-cv

Does anyone have real experience with Ornith-1.5-9B for coding

model-releasesr-localllama

I'm very happy with Qwen-3.8-27B, I run it on my work machine and switched for major part of real coding tasks from cloud subscriptions to it. I use one dedicated headless RTX 3090, and get maybe 1000

GRACE:Gradient-guided Coreset Selection for LLM Unlearning

arXiv:2608.28361v1 Announce Type: cross Abstract: Machine Unlearning methods for Large Language Models typically assume pre-specified forget and retain sets. In realistic settings, however, requests m

researcharxiv-cs-lg

Learning to Difference: Adaptive Reversible Differencing (AdaRDiff) for Time Series Forecasting

arXiv:2608.28134v1 Announce Type: new Abstract: Reliable long-horizon time series forecasting is an important yet difficult problem. Trends and seasonality introduce complex temporal structure that ch

Linux just got a local AI upgrade. 🐧 Congrats to @lmstudio on bringing Bionic to Linux, making it even easier to run local agents and open …

Linux just got a local AI upgrade. 🐧 Congrats to @lmstudio on bringing Bionic to Linux, making it even easier to run local agents and open models on NVIDIA hardware. Bionic is now available for Linux!

local-ailm-studio--x

Locate Anything in Videos: Rethinking Efficient Generative Spatio-Temporal Video Grounding

arXiv:2608.28192v1 Announce Type: new Abstract: Spatio-temporal video grounding (STVG) requires models to identify when a referred event occurs and localize the target entity throughout that interval.

local-aiarxiv-cs-cv

OmniFusion: Simultaneous Multilingual Multimodal Translations via Modular Fusion

arXiv:2512.00234v3 Announce Type: replace Abstract: There has been significant progress in open-source text-only translation large language models (LLMs) with better language coverage and quality. How

PersonaForge: Realistic Multi-Turn User Simulation for Agentic Systems

arXiv:2608.28378v1 Announce Type: new Abstract: Large language models are increasingly used as agentic workflow executors, yet existing training data and benchmarks largely assume informationally comp

RiskBlend: A Multi-Signal Framework for Test Input Prioritization in Machine Learning Regression Testing

arXiv:2608.27704v1 Announce Type: new Abstract: When machine learning classifiers are retrained, inputs correctly classified by the previous model version may be misclassified by the updated version,

local-aiarxiv-cs-lg

Run NVIDIA BioNeMo NIM Microservices for Protein Structure Prediction in Claude Science

model-releasesnvidia-developer

NVIDIA’s BioNeMo Agent Toolkit integrates over a decade of life‑science models and libraries into agent-callable skills, and when combined with Claude Science and NVIDIA NIM microservices it allows AI

Sliding-window beats linear attention

arXiv:2608.28444v1 Announce Type: new Abstract: Due to the nature of quadratic attention, Large Language Models (LLMs) consume a lot of memory and energy. Every new token costs more than the previous

The First Golden Age of AI writing is now over. For a brief period of time, many people were better off having Claude do a lot of their writ…

model-releasesethan-mollick--x

The First Golden Age of AI writing is now over. For a brief period of time, many people were better off having Claude do a lot of their writing, because it is a pretty good writer & AI detectors were

Safety

When Robots Mishear Us: Mapping the Safety Risks of Voice-Controlled Embodied AI

arXiv:2608.28518v1 Announce Type: cross Abstract: We investigate whether automatic speech recognition (ASR) errors in user input can lead to unsafe outputs from Embodied AI (EAI) models. We find that

safetyarxiv-cs-cl

FlashMLA sm_120 kernel build with 2-3x performance increase from SPDA