Search: “context”

World-Model-Grounded LLM Planning for AUV and ASV Navigation Near Offshore Wind Farms

model-releasesarxiv-cs-ro

arXiv:2608.19661v1 Announce Type: new Abstract: Large language models can turn a natural-language mission into a sequence of robot actions, but they do not have a sense of physics: they cannot judge h

21 Aug 2026

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Model Releases

YolovN-CBi: A Lightweight and Efficient Architecture for Real-Time Detection of Small UAVs

DGX agent

arXiv:2512.18046v2 Announce Type: replace Abstract: Unmanned Aerial Vehicles, commonly known as, drones pose increasing risks in civilian and defense settings, demanding accurate and real-time drone d

model-releasesarxiv-cs-cv

21 Aug 2026

Safety

A Metamorphic Artificial Age Score Decision-Support Prototype for Flight-Log-Based Drone Propeller Health Monitoring

arXiv:2608.18088v1 Announce Type: new Abstract: Drone propeller faults can create safety and reliability risks when their effects are distributed across multiple flight-log channels rather than appear

safetyarxiv-cs-ai

A Multi-Agent Platform for Automated Enterprise Analytics and Insight Generation

arXiv:2608.18740v1 Announce Type: new Abstract: This paper proposes a multi-agent framework built on CrewAI [1] for conversational business intelligence. Five specialized AI agents operate in a sequen

agentsarxiv-cs-ai

Tutorials

About the impact of grouping classes in multiclass classification [D]

tutorialsr-machinelearning

A premise: I hope this question is 'worth' of this subreddit, I did a decent amount of research before posting, I thought it was potentially interesting enough for it, but possibly not basic enough fo

Adaptive Multi-Agent Feature Selection for Personalized Fall Risk Prevention

arXiv:2608.18450v1 Announce Type: new Abstract: Falls among older adults represent a major public health challenge driven by complex, time-varying interactions across multiple risk domains. Effective

agentsarxiv-cs-lg

Tutorials

AI Can Learn Scientific Taste

arXiv:2603.14473v3 Announce Type: replace Abstract: Scientific discovery depends on expert judgement and foresight, which we call scientific taste: the ability to judge and propose research ideas with

tutorialsarxiv-cs-cl

Allocating Recurrent Compute in Looped Language Models

arXiv:2608.18230v1 Announce Type: new Abstract: Looped language models improve reasoning and knowledge manipulation by applying shared computation repeatedly. Existing systems usually repeat an entire

researcharxiv-cs-lg

An Empirical Benchmark of Deep Time-Series Models for Smart Meter Energy Forecasting

model-releasesarxiv-cs-lg

arXiv:2608.18675v1 Announce Type: new Abstract: Accurate forecasting of energy consumption is important for the efficient operation of power systems, with direct implications for operational costs, en

AQuA's 'self-improvement' updates research state, not the agent LM. What should a local port freeze?

AQuA's preprint uses 'recursive self-improvement' for a bounded research loop. It does not say the research-agent LM rewrites its own weights. The paper separates three objects: The language model dri

local-air-localllama

Beyond LLM-Based Reasoning: Lightweight GNNs for Agent Failure Attribution

arXiv:2608.18575v1 Announce Type: new Abstract: Large language model (LLM)-based multi-agent systems (MAS) often exhibit complex failure modes, which frequently cause agents to produce incorrect outco

Breaking the weakest link to evade vision language models

arXiv:2608.18938v1 Announce Type: new Abstract: Vision Language Models (VLMs) have recently emerged as a critical component of multimodal AI systems, enabling joint reasoning over visual and textual i

Compress and Forget: bitsandbytes Quantization Amplifies Proactive Interference in LLMs

arXiv:2608.18578v1 Announce Type: new Abstract: Proactive interference (PI) is a documented failure mode in large language models in which retrieval of a repeatedly overwritten value degrades as prior

CTIFoundry: An Agent-Native Corpus Scaffold for Cyber Threat Intelligence

arXiv:2608.18613v1 Announce Type: new Abstract: Cyber threat intelligence (CTI) is increasingly consumed not by human analysts but by LLM agents that compose multi-step investigations at query time. T

DeepTCM1.0: A Multi-Expert AI Agent for Deciphering Mechanisms of Chinese Herbal Formulae Based on General Large Language Models

arXiv:2608.18103v1 Announce Type: cross Abstract: Background: Mechanistic elucidation of traditional Chinese medicine (TCM) compound formulas remains a central challenge in the modernization of TCM. C

Designing Social Robots for Social-Cognition Training with Autistic Adults

arXiv:2608.18488v1 Announce Type: cross Abstract: Social robots have been widely explored as tools for autism intervention, yet this literature has focused predominantly on children and has rarely inv

applicationsarxiv-cs-ro

DocClaw: A Unified Agentic System for Intelligent Document Processing

arXiv:2608.18685v1 Announce Type: new Abstract: Intelligent document processing (IDP) encompasses a broad range of tasks, including optical character recognition (OCR), document question answering (Do

agentsarxiv-cs-cv

Hardware

EfficientSync: Real-Time Lip Synchronization via Deformation-Based Reference Texture Mixing

arXiv:2608.18832v1 Announce Type: new Abstract: Audio-driven lip synchronization manipulates the mouth region of a talking-face video to match the driving audio while preserving head pose, identity, a

hardwarearxiv-cs-cv

Eureka: Task-Conditioned Meta-Agent Orchestration for Scientific Discovery

arXiv:2608.19047v1 Announce Type: new Abstract: We present Eureka, a task-conditioned Meta-Agent architecture that compiles long-horizon tasks into dynamic obligation graphs with explicit acceptance s

local-aiarxiv-cs-ai

Event-Causal RAG: A Retrieval-Augmented Generation Framework for Long Video Reasoning in Complex Scenarios

arXiv:2605.06185v2 Announce Type: replace Abstract: Large vision-language models perform well on short- and medium-length video understanding but still struggle to maintain coherent event memory and r

FedLNS: Leverage LayerNorm Signature Modeling to Mitigate Adversarial Manipulation in Federated LLMs

model-releasesarxiv-cs-lg

arXiv:2608.18736v1 Announce Type: new Abstract: Federated training enables language models to learn from distributed private text, but the server cannot directly verify the local supervision or optimi

Flama: a Python framework for development and deployment of production-ready APIs, machine learning, and LLM services

arXiv:2608.18733v1 Announce Type: cross Abstract: We present Flama, an open-source Python framework for developing and deploying production-ready web APIs, machine learning services, and large-languag

local-aiarxiv-cs-ai

From Threat Intelligence to Detection: Knowledge-driven Enrichment and Template-based Rule Grounding for Automated Sigma Rule Generation

arXiv:2608.19011v1 Announce Type: cross Abstract: Mechanisms for dynamically converting cyber threat intelligence (CTI) into actionable detection capabilities are necessary due to the rapid evolution

applicationsarxiv-cs-ai

GLM 5.3 SlopCodeBench Results

model-releasesr-localllama

Howdy once again, I had a request to try out 5.3 on the benchmarks - they're unsaturated so it's a fun test right now! This one was interesting because I accidentally ran it on all 36 problems (rip 20

Gradient Mirage: Trainable yet Label-Unidentifiable Gradients in Large Language Model Split Learning

arXiv:2608.18767v1 Announce Type: new Abstract: Gradient matching attacks (GMAs) in LLM split learning (SL) rely on a critical yet underexplored assumption: the gradient exposed at the split interface

researcharxiv-cs-cl

home lab assistant llm

hey so im currently working to integrate a locally ran llm to control home assistant (through tool calling, no direct connection) so i can use a voice input without needing very specific commands. Its

local-air-ollama

Hardware

How Generative Recommenders Are Redefining RecSys at Scale

Generative recommenders (GRs) replace traditional embedding‑based methods with transformer‑style sequence models like HSTU and Semantic IDs, addressing scalability, cold‑start, and long‑tail issues in

hardwarenvidia-developer

Human-Centric Intelligence in the Era of Foundation Models: A Survey

arXiv:2608.18184v1 Announce Type: new Abstract: Human-centric intelligence is evolving in the foundation-model era, with growing emphasis on scale, transferability, and general-purpose modeling. Yet i

researcharxiv-cs-cv

I built a visual multi-agent workflow editor that exports runnable CrewAI code — here’s a 5-agent workflow running locally with Ollama

I've been building AgentGraph Studio, a visual editor for designing multi-agent workflows and exporting them as runnable Python code. One thing I wanted to verify was whether the generated code actual

model-releasesr-ollama

Institutional Books - Visual Elements: An open-source pipeline for extracting, classifying, deduplicating, and captioning visual elements from digital book collections

arXiv:2608.18957v1 Announce Type: new Abstract: Historical book collections contain rich visual elements - such as illustrations, photographs, engravings, and decorative art - that are frequently unde

researcharxiv-cs-cv

Is it possible to fine-tune gemma4 A4B to generate complex legal principles of court decision? [D]

model-releasesr-machinelearning

I have a big database of local court decisions with a legal sentence which is like a paragraph summary of the doc. I've been tinkering with FTing for many days now, all results inconclusive never beat

LACONIC: Dense-Level Effectiveness for Scalable Sparse Retrieval via a Two-Phase Training Curriculum

arXiv:2601.01684v2 Announce Type: replace-cross Abstract: While dense retrieval models have been the standard for state-of-the-art information retrieval, their deployment is often constrained by high

Safety

Learned, Then Lost: A Measured Single-Example Counterfactual in Pre-training

arXiv:2608.19168v1 Announce Type: new Abstract: A single training example's contribution to a finished model is normally estimated rather than measured, because measuring it takes two expensive full p

safetyarxiv-cs-lg

LEDGER: Claim-to-Evidence Trace Graphs for Auditing LLM Agents

arXiv:2608.18398v1 Announce Type: cross Abstract: Large language model (LLM) agents can now carry out long-horizon technical workflows involving complex tool use, code execution, file edits, and gener

agentsarxiv-cs-ai

Ling-3.0 released all 6 base checkpoints: 2 sizes × 3 stages

model-releasesr-localllama

AntLing has released the full six-checkpoint matrix for the Ling-3.0 base model. tiny: pretrained, mid-trained, WSM-merged flash: pretrained, mid-trained, WSM-merged The concrete artifact is six separ

Mapping intrinsic rank and informational gravity in complex tabular data: I developed a non-parametric, model-agnostic, information-theoretic diagnostic to bypass the limits of linear, rank, and Euclidean baselines. [R]

applicationsr-machinelearning

Links: Preprint: https://doi.org/10.5281/zenodo.22028087 Entropic Scree Function v1.0.0 / GitHub: https://github.com/tjleestjohn/Entropic-Scree TL;DR: Standard PCA fundamentally fractures non-linear d

Mechanistic Interpretability of Structure-Aware Numerical Reasoning in LLaMA 3.1 8B

arXiv:2608.18419v1 Announce Type: cross Abstract: Recent work has shown that large language models (LLMs) exhibit strong numerical sequence modeling capabilities and show promise in time-series predic

MissDiag: Diagnostic Evaluation of Incomplete-Knowledge Robustness in KGQA and KG-RAG

arXiv:2608.18489v1 Announce Type: new Abstract: Knowledge graph question answering (KGQA) and knowledge-graph-based retrieval-augmented generation (KG-RAG) aim to ground answers in explicit graph evid

Model Card for OpenAI Privacy Filter

model-releasesarxiv-cs-lg

arXiv:2608.18274v1 Announce Type: cross Abstract: OpenAI Privacy Filter is a compact, bidirectional token-classification model for detecting and redacting personally identifiable information (PII) and

One Gate Is Not Enough: Composing Stateful Pre-Action Controls for Agentic AI

arXiv:2608.18360v1 Announce Type: cross Abstract: Agentic AI systems take consequential actions governed by more than one pre-action control at once: authority, resource, and evidence gates that can a

agentsarxiv-cs-ai

Online Conformal Anomaly Detection with Prediction-Powered Data Acquisition

arXiv:2505.01783v2 Announce Type: replace Abstract: Online anomaly detection is essential in fields such as cybersecurity, healthcare, industrial monitoring, and telecommunications, where promptly ide

applicationsarxiv-cs-lg

Open-MOPD: Diagnosing and Fixing Capability Imbalance in Multi-Teacher On-Policy Distillation

arXiv:2608.19098v1 Announce Type: cross Abstract: Multi-teacher on-policy distillation (M-OPD) has emerged as a promising paradigm for consolidating domain-specialized reinforcement learning (RL) expe

PATE-Forensics: Perception-as-Tool for Explainable Deepfake Forensics with General-Purpose MLLMs

arXiv:2608.18573v1 Announce Type: new Abstract: Existing explainable deepfake forensic methods typically rely on task-adapted MLLM to jointly address detection, localization, and explanation. Inspired

local-aiarxiv-cs-cv

Safety

Pretraining Reusable Inference Across Views with Synthetic Task Priors

arXiv:2608.19115v1 Announce Type: new Abstract: Modern pretrained encoders make representations from heterogeneous views increasingly reusable, but the procedure that determines view utility and combi

safetyarxiv-cs-lg

Qwen3.8-27B scored 29/30 on AIME 2026 with FP8 + xhigh reasoning — BF16 vs FP8 results

model-releasesr-localllama

I benchmarked Qwen3.8-27B on MathArena/aime_2026 dataset, comparing BF16 and FP8 weights at medium and xhigh reasoning effort. Interesting findings are: quantized FP8 xhigh is better than BF 16 medium

Revisiting the 'Push-T' Robot Manipulation Task with Agentic Robotics

model-releasesarxiv-cs-ro

arXiv:2608.18227v1 Announce Type: new Abstract: Push-T is an iconic benchmark for learning manipulation policies from human demonstrations. The robot must use a single point of contact to push a T-sha

Tutorials

Role-Conditioned Sub-Token Routing for Efficient Vision-Language-Action Policies

arXiv:2608.18410v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models process long multimodal token sequences, making inference expensive in both memory and computation. Existing efficie

tutorialsarxiv-cs-lg

Scheduling and Routing with Degradation-Triggered Job Arrivals: An Application to Forest Firefighting with an Unmanned Aerial Vehicle Fleet

arXiv:2608.18140v1 Announce Type: new Abstract: We define an intertwined scheduling and routing problem where new jobs appear due to the degradation of the existing jobs. Specifically, once a job arri

applicationsarxiv-cs-ro