Search: “deployment”

SurakshaEval: An Indic Safety Benchmark for Multilingual LLMs

arXiv:2608.07862v1 Announce Type: new Abstract: Existing safety evaluation datasets for large language models (LLMs) predominantly focus on English and Western contexts, often overlooking the linguist

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SurgLAT: Surgical Latent Attention Tracking for Depth-Aware Robotic Laparoscope Control

DGX agent

arXiv:2608.07876v1 Announce Type: new Abstract: Autonomous laparoscopic camera control requires continuous understanding of the surgeon's operative intent in dynamic surgical scenes, where the target

agentsarxiv-cs-ai

11 Aug 2026

SwissCrop25: A National Multi-Year Benchmark for Operational Crop Mapping

model-releasesarxiv-cs-cv

arXiv:2608.09497v1 Announce Type: new Abstract: Operational crop mapping requires models that generalise across years, resolve fine-grained crop taxonomies, and distinguish cropland from surrounding l

Targeted Counterfactual Fingerprinting for Black-Box LLM Ownership Verification

arXiv:2608.08195v1 Announce Type: cross Abstract: Large language models (LLMs) are high-value assets that can be derived through redeployment, fine-tuning, quantization, or further alignment. Because

local-aiarxiv-cs-ai

Task-Oriented Formation Decision via Reinforcement Learning: Herding an Attacking Swarm

model-releasesarxiv-cs-ro

arXiv:2608.09258v1 Announce Type: new Abstract: Multi-robot systems can accomplish tasks that are difficult for a single robot by organizing into task-specific formations. Different from existing stud

TDMA Based Communications Control Co-Design for Cooperative Carrying: Delay Calibration and Sampling-Rate Optimization

arXiv:2608.09556v1 Announce Type: new Abstract: Multi robot teams performing cooperative transportation face a fundamental challenge: maintaining stable control while keeping communications efficient.

applicationsarxiv-cs-ro

Temporal Generalization in fNIRS-Based Autism Classification: A Cross-Time-Window Transfer Benchmark

arXiv:2608.07567v1 Announce Type: cross Abstract: Functional near-infrared spectroscopy (fNIRS) is a promising modality for autism spectrum disorder (ASD) classification, yet existing approaches assum

Test-Time Augmentation for LLMs: When Input Diversity Beats Output Diversity at Matched Compute

arXiv:2608.09351v1 Announce Type: cross Abstract: Test-time scaling improves LLM accuracy but multiplies inference cost, making the accuracy gained per unit of compute the metric that matters in deplo

researcharxiv-cs-ai

Tevatron-Elastic: A Unified Abstraction for Training Elastic Retrievers and Rerankers

arXiv:2608.08809v1 Announce Type: new Abstract: A single model scale challenges the flexibility of a production retrieval system: some settings need it faster, others need a smaller index, and the rig

The Collaboration Gap: Exploration and Benchmarking of Open-World Agentic Cooperation

arXiv:2511.02687v2 Announce Type: replace Abstract: The trajectory of AI development suggests that we will increasingly rely on agent-based systems powered by language models, composed of independentl

The Neural Division of Labor: Biologically-Inspired Modular Architectures for Robust Neuromorphic Computing

arXiv:2608.08317v1 Announce Type: new Abstract: Biological neural systems achieve high efficiency and robustness through compartmentalized architectures. In contrast, modern artificial neural networks

researcharxiv-cs-lg

The Scaling Paradox in Human-AI Collaboration

arXiv:2608.00818v2 Announce Type: replace Abstract: The discovery of scaling laws has highlighted the extraordinary potential of AI systems with a striking empirical pattern: as AI systems scale, thei

The Theory of Strategic Evolution: Games with Endogenous Players and the Seven Laws of Strategic Replicators

arXiv:2512.07901v4 Announce Type: replace-cross Abstract: Von Neumann founded both game theory and the theory of self-reproducing automata, but the two programs never merged. Rational players do not c

The Watermark Shortcut: How Provenance Marking Sabotages Audio Deepfake Detection

arXiv:2606.23335v2 Announce Type: replace-cross Abstract: Provenance watermarking is increasingly treated as a safeguard for synthetic speech, whether built directly into speech-generation models such

researcharxiv-cs-ai

Towards Realistic Guarantees: A Probabilistic Certificate for SmoothLLM

arXiv:2511.18721v4 Announce Type: replace-cross Abstract: The SmoothLLM defense provides a certification guarantee against jailbreaking attacks, but it relies on a strict 'k-unstable' assumption that

Towards Researcher Agents for Knowledge-Graph Question Answering

arXiv:2608.07700v1 Announce Type: new Abstract: Translating a natural-language question into a SPARQL query that can be executed against a large knowledge graph requires resolving lexical ambiguity, g

TreeHop: Efficient Embedding-Level Query Rewriter

arXiv:2504.20114v3 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) systems face significant challenges in multi-hop question answering (MHQA), where complex queries require

Understanding Calibration and Truncation Error Propagation in Training-Free Low-Rank Compression for LLMs

arXiv:2608.08506v1 Announce Type: new Abstract: Training-free low-rank compression frameworks have been gaining prominence for LLM compression given their effectiveness in reducing model parameter cou

UniMoMo: Expert Merging-Based MoE Acceleration for Large Recommendation Models

arXiv:2608.08627v1 Announce Type: new Abstract: Sparse mixture-of-experts (MoE) layers expand recommendation capacity through conditional computation, yet a trained checkpoint still stores and routes

VectraYX-Vision-1B: A Sub-2B Spanish/LATAM Cybersecurity Vision-Language Model with Structured Visual Reasoning and Native Tool Use

arXiv:2608.08477v1 Announce Type: new Abstract: We present VectraYX-Vision-1B, a sub-2B vision-language model (VLM) for Spanish/LATAM cybersecurity imagery, coupling a frozen SigLIP-so400m encoder to

Vid2WAM: Distilling Video Diffusion Priors into World Action Models

arXiv:2608.08558v1 Announce Type: new Abstract: World Action Models (WAMs) improve robot policy learning by jointly modeling future visual dynamics and actions. However, their scalability and generali

safetyarxiv-cs-ro

Visual Distortion Detection in UGC Images Using Large Multimodal Models

arXiv:2608.09122v1 Announce Type: cross Abstract: The localized depiction of perceptual quality has long been a crucial, yet underexplored, challenge in image quality assessment (IQA). Existing approa

Weather- and Location-Aware Agentic Dining Recommendation: Leveraging LLM World Knowledge for Region-Sensitive Contextual Reasoning

arXiv:2608.07593v1 Announce Type: cross Abstract: Context-aware recommender systems have long recognized that factors such as location, time, and weather shape where and what people choose to eat. Exi

local-aiarxiv-cs-ai

When LLM Agents Negotiate: Private Information and Dynamic Bargaining in Supply Chains

arXiv:2608.07538v1 Announce Type: new Abstract: As LLM agents move from decision support to autonomous procurement, firms need to know whether delegated negotiators create value, divide it predictably

ZOMP: Zeroth-Order Multi-Modal Prompt Tuning for Vision-Language Models

arXiv:2608.08060v1 Announce Type: new Abstract: Fine-tuning vision-language models such as CLIP typically requires backpropagation (BP) through the full model, which is infeasible when only forward-pa

researcharxiv-cs-cv

A MARL Centered Reference Architecture for Large Language Model Augmentation in Smart Manufacturing

arXiv:2608.07148v1 Announce Type: new Abstract: Modern manufacturing imposes six coupled demands on adaptive control: local decisions with global consequences, partial observability, nonstationarity,

local-aiarxiv-cs-ai

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

AfriNLLB: Efficient Translation Models for African Languages

arXiv:2602.09373v2 Announce Type: replace Abstract: In this work, we present AfriNLLB, a series of lightweight models for efficient translation from and into African languages. AfriNLLB supports 15 la

researcharxiv-cs-cl

AutoIntervene: Calibrated Intervention for Action-Chunking Imitation Learning Policies

arXiv:2608.07065v1 Announce Type: cross Abstract: Action-chunking visuomotor policies learn from demonstrations and improve temporal consistency by predicting short action sequences rather than single

Autonomy-of-Heads: Data-Free Sparse Attention from Frozen Query-Key Geometry

arXiv:2608.06849v1 Announce Type: cross Abstract: Long-context LLM inference is bottlenecked by quadratic attention computation and growing KV-cache costs. Existing sparse attention and KV-compression

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction

arXiv:2608.07420v1 Announce Type: new Abstract: World models are expected to support imagination over extended temporal horizons, yet most are still trained through local few-step prediction objective

local-aiarxiv-cs-lg

Casting the Net! Revisiting MasterFace Impersonation Attacks

arXiv:2608.06952v1 Announce Type: cross Abstract: Impersonation is a fundamental security threat in face recognition systems (FRSs). While the security of FRSs has been challenged by various attack ve

applicationsarxiv-cs-cv

Characterizing the Quality Profile of AI-Generated C++ in Production

arXiv:2608.06640v1 Announce Type: cross Abstract: The widespread integration of AI coding assistants offers undeniable boosts to engineering velocity. Yet, recent studies point to a growing trade-off,

Agents

CloudDiffusion: Diffusion-Based Scene Completion in the Point Cloud Domain

arXiv:2606.16048v3 Announce Type: replace Abstract: Reconstructing dense 3D scenes from sparse LiDAR point clouds (LiDAR scene completion) is a fundamental challenge in autonomous driving, where diffu

agentsarxiv-cs-cv

CoDAT: Collaborative Dual-Attention Transformer with Low-Cost Temporal Modeling for Efficient Edge Action Recognition

model-releasesarxiv-cs-cv

arXiv:2608.06691v1 Announce Type: new Abstract: Real-time human action recognition on Internet-of-Things (IoT) edge devices requires models that capture rich spatio-temporal cues within strict latency

Conformal Coverage Guarantees for Any Video Temporal Grounder

arXiv:2608.07434v1 Announce Type: new Abstract: Event boundaries in continuous video are ambiguous: re-annotate the same query-video pair and independent annotators mark moments that overlap by less t

local-aiarxiv-cs-cv

Critical Acclaim Orientation in Large Language Models: Evidence from Film Preference Elicitation

arXiv:2608.06955v1 Announce Type: new Abstract: Large language models (LLMs) are trained on corpora that contain expressions of human judgment about films, books, music, and more. Yet whether LLMs sys

CrossTracer: Cross-Embodiment Navigation via VLA Model Reasoning and Trace Residuals Adapting

model-releasesarxiv-cs-ro

arXiv:2608.06688v1 Announce Type: new Abstract: Vision-language-action (VLA) models provide strong semantic priors for robot navigation, but they often ignore embodiment-specific mobility constraints.

Curriculum as Code: An AI-Assisted Architecture for Instructional Design in STEM Education

arXiv:2608.07364v1 Announce Type: new Abstract: Contribution: This paper presents a six-phase AI-assisted instructional design architecture based on the Curriculum as Code paradigm, integrating Genera

Depth-Wise Probing and Pruning of the Planning Token in a Driving Vision-Language-Action Model

arXiv:2608.07361v1 Announce Type: cross Abstract: Vision-language-action (VLA) models route driving decisions through a deep language model, but it is unclear how much of that depth the action itself

researcharxiv-cs-cv

Do 3D Medical Foundation Models See Through MRI Artifacts? A Controlled Study of Representation Robustness

arXiv:2608.06613v1 Announce Type: cross Abstract: Self-supervised 3D medical foundation models are increasingly used as general-purpose feature extractors, yet their sensitivity to MRI artifacts remai

Do Audio Language Models Use Paralinguistic Evidence? Counterfactual Audits for Response Evaluation

arXiv:2608.06718v1 Announce Type: new Abstract: Audio-language models (ALMs) are increasingly used as judges for speech-to-speech systems, but a judge that receives audio may not actually use paraling

Dual-Node NVIDIA DGX Spark over Tailscale: A Remote-Access Testbed for Distributed LLM Training and Cyber-Threat-Intelligence Fine-Tuning

arXiv:2608.07226v1 Announce Type: cross Abstract: Compact AI systems make local language-model experimentation increasingly accessible, yet practical evidence for multi-node training on desktop-class

local-aiarxiv-cs-lg

GeoDistill-Refine: Silhouette-First Geometry Distillation for Annotation-Free Spacecraft Segmentation

arXiv:2608.07405v1 Announce Type: cross Abstract: Foundation segmentation models can provide supervision for spacecraft imagery without manual training masks, but their predictions vary with textual p

researcharxiv-cs-ai

How Malachyte solves retail’s cold-start problem with managed real-time AI

What’s the best way to recommend products to little-known users? We’ve spent our careers trying to solve this problem for major companies like Spotify and Priceline, and it’s why Sidd founded Malachyt

local-aigoogle-cloud-ai

I compared GGUF quants of Qwen3.6 27B to NVFP4, AWQ, AutoRound, and FP8

model-releasesr-localllama

There's an interactive chart and some extra data in the blog post if you're interested. There are plenty of KL-divergence benchmarks for GGUF models, but most of them compare one GGUF quant against an

Impressive new paper from Meta. (bookmark it) Scaling laws assume model size and training data act on loss independently. This work introduc…

Impressive new paper from Meta. (bookmark it) Scaling laws assume model size and training data act on loss independently. This work introduces Skaling law, which couples capacity and data through a si

researchdair-ai--x

Let's Unlearn Stereotypes Before Decision-Making: Assessing the Impact of Intrinsic Bias Mitigation on Downstream Fairness in LLMs

arXiv:2509.16462v2 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly used in high-stakes decision-making systems, where biased predictions can reinforce social and economi

safetyarxiv-cs-cl