Search: “routing”

DocPure: Prompt-Free Unified Document Restoration via Degradation-Aware Structure-Guided Wavelet Modulation

arXiv:2608.09536v1 Announce Type: new Abstract: High-quality document images are pivotal for information archiving and downstream automatic processing. However, they are frequently compromised by dive

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Agents

Dynamic Coalition Formation and Communication Pricing in Skill-Based Agentic AI Systems

DGX agent

arXiv:2608.07532v1 Announce Type: new Abstract: Modern agentic AI systems combine multiple large language model agents with heterogeneous skills, yet most architectures either fix communication in adv

agentsarxiv-cs-ai

11 Aug 2026

FEAST: Federated Shared-Space Training for Resource-Heterogeneous Clients

model-releasesarxiv-cs-lg

arXiv:2608.09250v1 Announce Type: new Abstract: Federated learning (FL) must serve devices with varying computational capabilities. A fixed model cannot suit all devices, while training one model per

Industry

Frontier AI raises the cybersecurity bar: Why prediction must become prevention

Artificial intelligence is a double-edged sword when it comes to cybersecurity. It is giving defenders new ways to sift through vast amounts of telemetry, identify anomalous behavior and automate rout

industrysiliconangle

Geometry Beats Estimated Depth: RGB-Only Multi-Camera 3D Tracking under Sim2Real

arXiv:2608.07579v1 Announce Type: cross Abstract: The AI City Challenge 2026 Track 1 evaluates multi-camera 3D perception in large indoor warehouses under a synthetic-to-real (Sim2Real) setting; depth

Safety

KumbhDoot: A Scale-Ready, LLM-Bounded Architecture for Mass-Gathering Public-Service Assistants

arXiv:2608.07520v1 Announce Type: cross Abstract: Mass religious gatherings such as the Kumbh Mela concentrate tens of millions of people into a single region over a few weeks, producing intense, repe

safetyarxiv-cs-ai

Applications

LineGraph2Road: Structural Graph Reasoning on Line Graphs for Road Network Extraction

arXiv:2602.23290v2 Announce Type: replace Abstract: Extracting routable road networks from satellite imagery requires accurate topology recovery beyond pixel-level segmentation. Recent methods decompo

applicationsarxiv-cs-cv

A Picture is Worth a Thousand Tokens: How Vision Language Models Cut AI Energy Costs While Improving Accuracy

arXiv:2608.07427v1 Announce Type: new Abstract: LLM inference accounts for over 90% of AI operational energy, scaling directly with input token count---a critical inefficiency for telecom network anal

CyberForge: Verified Vulnerability Injection at Repository Level for Cybersecurity Agent Training

arXiv:2608.06471v1 Announce Type: cross Abstract: Despite recent advances, frontier large language model (LLM) agents remain limited in discovering and patching complex vulnerabilities in real-world s

HNR-DAC: Hard-Negative Reranking and Distribution-Aligned Classification for Scientific Claim Verification

arXiv:2608.07204v1 Announce Type: new Abstract: Scientific claim verification over a cited paper requires predicting the claim--paper relation and identifying the paragraphs that justify that predicti

Tutorials

LoRAScan: Detecting Backdoor Prompts in Low-Rank Adapters for Large Language Models via Down-Projection Activation Spikes

arXiv:2608.06795v1 Announce Type: cross Abstract: Low-rank adaptation (LoRA) enables efficient specialization and distribution of large language models through compact adapters. However, untrusted ada

tutorialsarxiv-cs-ai

RoRA: Role-Oriented Regional Allocation for Visual Token Pruning in MLLMs

arXiv:2608.07088v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) encode images as long visual token sequences, making prefilling and KV-cache storage expensive. Existing trai

Soft Redaction of Image Provenance via Zero-Knowledge Proofs

arXiv:2608.07063v1 Announce Type: cross Abstract: Content provenance standards, such as C2PA, are increasingly used to attach signed records of origin, editing history, and rights to digital images. H

I tested a fresh GitHub download → Ollama → first local coding-agent task (72 seconds, no cloud API)

I’m building DesktopLab, an open-source local-first control plane for development agents. I recorded the setup boundary that most agent demos skip: DesktopLab detects the host, proposes the supported

model-releasesr-ollama

8 Aug 2026

Arbitrage: Efficient Reasoning via Advantage-Aware Speculation

researchapple-ml-research

Modern Large Language Models achieve impressive reasoning capabilities with long Chain of Thoughts, but they incur substantial computational cost during inference, and this motivates techniques to imp

Constraint-First Reasoning: A Training-Free Protocol for Exploiting Answer-Space Constraints in Mathematical Problem Solving

arXiv:2608.05254v1 Announce Type: new Abstract: Large language models can derive a plausible mathematical object yet still violate explicit requirements--for example, by omitting a modular reduction,

Local Ai

EdgeXpert: An Edge Device for Memory-Efficient LLM Inference with Mixture-of-Experts and Speculative Decoding

arXiv:2608.05303v1 Announce Type: cross Abstract: On-device deployment of Large Language Models (LLMs) has become essential for personalized edge applications. A primary bottleneck is external memory

local-aiarxiv-cs-cl

OrchestraBench: Evaluating Multi-Agent Orchestration Failure Modes, Recovery, and Decomposition Quality

arXiv:2608.05263v1 Announce Type: new Abstract: Multi-agent orchestration frameworks are moving from demos to production, yet benchmarks typically report task accuracy without diagnosing why a pipelin

StyleComposer: Training-Free Multi-Reference Style Composition

arXiv:2608.05213v1 Announce Type: new Abstract: The style of a painting is not monolithic: color, texture, and structure may come from different sources. Existing reference-guided methods transfer the

researcharxiv-cs-cv

Personalized Federated Sparse Adaptation of Time-Series Foundation Models

arXiv:2608.04695v1 Announce Type: cross Abstract: Federated adaptation of time-series foundation models (TSFMs) is attractive for building energy forecasting because meter data are private, distribute

6 Aug 2026

Talk2Sensors: 3D Visual Grounding in Autonomous Driving via Sensor-Adaptive Physical Cue Matching

model-releasesarxiv-cs-cv

arXiv:2608.04568v1 Announce Type: new Abstract: As a key capability for embodied intelligence, 3D visual grounding (3DVG) has been predominantly studied in indoor scenes with RGB-D or point-cloud inpu

6 Aug 2026

Agents

When Shared Rollouts Fail in Defensive Driving Evaluation: A NAVSIM Score Basis Audit

arXiv:2608.04896v1 Announce Type: new Abstract: Defensive driving scores are useful only when they preserve distinctions between policies that observe surrounding actors and those that do not. Re-simu

agentsarxiv-cs-ai

6 Aug 2026

Hardware

AcceptMoE: Commitment-Weighted Self-Sizing Verifier Expert Sets for Efficient MoE Speculative Decoding

arXiv:2608.02989v1 Announce Type: cross Abstract: Speculative decoding verifies a tree of draft tokens in one target-model forward pass. For a mixture-of-experts (MoE) target, however, parallel verifi

hardwarearxiv-cs-cl

CrossScope: A Role-Asymmetric World Model for Joint Dual-Scope Surgical Video Prediction

model-releasesarxiv-cs-cv

arXiv:2608.03211v1 Announce Type: new Abstract: Visual world models typically learn future dynamics from a single observation stream, limiting their ability to model cooperative systems with multiple

FedRings: A Scalable and Topology-Aware Federated Learning Framework for LEO Satellite Constellations

arXiv:2608.03436v1 Announce Type: cross Abstract: Federated learning over low Earth orbit (LEO) satellite networks is limited by frequent link changes, short contact times, and a highly dynamic topolo

researcharxiv-cs-lg

Local Ai

Keep the Needle, Prune the Haystack: Defect-Preserving Token Pruning for Efficient Zero-Shot Anomaly Detection

arXiv:2608.03681v1 Announce Type: new Abstract: Zero-shot visual anomaly detection has achieved remarkable progress, with recent vision-only approaches further improving performance while simplifying

local-aiarxiv-cs-cv

Reachability Is Not Realization: Tracing the Sources of LLM Benchmark Gains

arXiv:2608.03219v1 Announce Type: new Abstract: Benchmark gains are often treated as evidence of greater LLM capability. Yet the same gain can reflect different changes in model behavior. A model may

UniEvo-RS: Omni-Prompt Unified Remote Sensing Segmentation with Representative Exemplar-Driven Prototype Evolution

arXiv:2608.03911v1 Announce Type: new Abstract: Prompt-driven vision-language models (VLMs) hold immense promise for accelerating dense remote sensing (RS) annotation, but static models suffer from se

researcharxiv-cs-cv

BiKAN: Restoring Collapsed Basis of Binary Kolmogorov--Arnold Networks

model-releasesarxiv-cs-lg

arXiv:2608.01490v1 Announce Type: new Abstract: Binarizing a polynomial Kolmogorov--Arnold Network (KAN) not only changes parameter precision, but also alters the function space available to each laye

CARNet: Channel-Adaptive Receiver Network for Robust NextG Communications

arXiv:2608.02172v1 Announce Type: cross Abstract: Neural receivers have been recognized as a promising paradigm for the next-generation (NextG) communications. However, due to the reliance on a static

researcharxiv-cs-lg

[Deepseek-V4-Flash-0731] Full 1M context on a single RTX5090 + DDR5 Desktop Setup with VLLM CPU/Ram Offloading, ~800 tps pp & 15+ tps decode [Agentic Coding]

model-releasesr-localllama

First of all, obviously I took some help from AI to type this post and this is the topic that enabled me to accomplish all that: https://old.reddit.com/r/LocalLLaMA/comments/1veow4b/deepseek_v4flash_2

Applications

Don't Offer What Can't Be Done: Deterministic Executability Gating for LLM Skill Selection at Scale

arXiv:2608.01050v1 Announce Type: cross Abstract: Production LLM agents that select from large skill libraries face a limitation that semantic relevance alone cannot resolve: a skill may match a user'

applicationsarxiv-cs-cl

Global Optimization and Inference-Time Region Grafting for Agentic Workflows

arXiv:2608.02353v1 Announce Type: new Abstract: Recent advances in agentic workflow optimization automate workflow design through task-specific workflow search or input-conditioned architecture select

Illuminating Visual Identity in Universal Multimodal Embeddings

arXiv:2608.01794v1 Announce Type: cross Abstract: Universal Multimodal Embeddings (UMEs) aim to unify various modalities and tasks into a shared representation space. In recent years, this field has w

Linear Multi-Timescale Retention as a Memory-Efficient Vision-Language Bridge

model-releasesarxiv-cs-cv

arXiv:2608.01614v1 Announce Type: new Abstract: Vision-Language Models (VLMs) face a critical computational bottleneck when processing high-resolution imagery due to the O(N^2) memory complexity of So

LLM generation novelty through the lens of semantic similarity

arXiv:2510.27313v3 Announce Type: replace-cross Abstract: Generation novelty is a key indicator of an LLM's ability to generalize, yet measuring it against full pretraining corpora is computationally

Revisiting Generalization Across Difficulty Levels: It's Not So Easy

arXiv:2511.21692v2 Announce Type: replace Abstract: We investigate how well large language models (LLMs) generalize across different task difficulties, a key question for effective data curation and e

SERL-SQL: Selective Hindsight Distillation for Text-to-SQL Reinforcement Agentic Learning

arXiv:2608.00485v1 Announce Type: new Abstract: Recent Text-to-SQL systems increasingly rely on multi-turn interaction, execution feedback, and reinforcement learning. However, most existing methods u

SLMs as Multi-Agent Routers: A Progressive SFT and Reinforcement Learning Approach

arXiv:2608.00030v1 Announce Type: new Abstract: Specialised retrieval agents typically surface higher quality results than general-purpose search, but selecting the optimal agent for a given query rem

TrimMoE A communication aware and adaptive depth framework for distributed edge inference

arXiv:2608.00573v1 Announce Type: cross Abstract: Serving Mixture-of-Experts (MoE) large language models across distributed edge servers is bottlenecked by the cross-server expert transmission. The ex

Understanding Sparse Attention Selectivity in Long-Context Foundation Models via Counterfactual Evaluation

arXiv:2608.01676v1 Announce Type: new Abstract: Sparse attention is widely deployed in long-context serving stacks, yet no framework audits how discarding blocks changes the influence of specific cont

Agentic Harness for Real-World Compilers

arXiv:2603.20075v2 Announce Type: replace-cross Abstract: Compilers are critical to modern computing, yet fixing compiler bugs is difficult. While recent large language model (LLM) advancements enable

Cross-Resolution Semantic Learning for Graph Domain Adaptation

arXiv:2607.29365v1 Announce Type: new Abstract: Graph Domain Adaptation (GDA) transfers predictive knowledge from labeled source graphs to unlabeled target graphs under distribution shift. Existing me

researcharxiv-cs-lg

DeepSeek V4-Flash (284B MoE) at 33 tok/s single / 68 tok/s aggregate on 2× RTX 3090 + a used quad-Xeon DDR4 server — full config

model-releasesr-localllama

Ran DeepSeek V4-Flash-0731 — the full official checkpoint, not a re-quant — on commodity used hardware. Sharing because I couldn't find anyone else publishing Ampere results for this engine. Why bothe

Dense Temporal Contrast Synthesis via Conditioned Latent Transport

arXiv:2607.29394v1 Announce Type: cross Abstract: Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is essential for breast cancer management, but reliance on gadolinium-based contrast ag

RAID: Towards Robust AI-Generated Image Detection with Bit-Reversed Images

arXiv:2607.28974v1 Announce Type: cross Abstract: The rapid advancement of image generation models has made it increasingly difficult for people to distinguish AI-generated images from real ones. To p

Safety

SAF-OPD: Stable Advantage Fusion for On-Policy Distillation

arXiv:2607.29209v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) broadcasts a single response-level reward to every token, while on-policy distillation (OPD) sco

safetyarxiv-cs-ai

Safety

Understanding Alignment in Multimodal LLMs: A Comprehensive Study

Preference alignment has become a crucial component in enhancing the performance of Large Language Models (LLMs), yet its impact in Multimodal Large Language Models (MLLMs) remains comparatively under

safetyapple-ml-research