Search: “papers”

Attention, Anomalies! Handling Attention Layers in Unsupervised Federated Outlier Detection

arXiv:2608.04753v1 Announce Type: new Abstract: Attention layers are the backbone of today's most powerful and impactful models. Models with multi-million and billion parameters rely on contextual kno

Attention Fusion for Bridge Deck Delamination Detection

DGX agent

arXiv:2512.20113v4 Announce Type: replace Abstract: Subsurface delaminations in reinforced concrete bridge decks escape conventional visual inspection, and the two principal sensing techniques used to

safetyarxiv-cs-cv

6 Aug 2026

Beyond the QBER Threshold: A Temporal QBER Based Machine Learning Framework for Multi Attack Detection in BB84 QKD

arXiv:2608.04047v1 Announce Type: cross Abstract: Conventional BB84 Quantum Key Distribution (QKD) systems rely on a fixed 11% Quantum Bit Error Rate (QBER) threshold to detect eavesdropping. However,

Can Post-Training Transform LLMs into Causal Reasoners?

arXiv:2602.06337v2 Announce Type: replace-cross Abstract: Causal inference is essential for decision-making but remains challenging for non-experts. While large language models (LLMs) show promise in

ColorFD: A Finite-Difference Guided Black-Box Physical Adversarial Attack for Remote Sensing Object Detection

arXiv:2608.04559v1 Announce Type: new Abstract: Although deep neural network-based remote sensing object detectors have achieved strong performance, they remain vulnerable to adversarial perturbations

researcharxiv-cs-cv

Cooking beyond Frames: A Stereo Event Camera Dataset in the Kitchen

arXiv:2608.04865v1 Announce Type: new Abstract: Event cameras, also known as neuromorphic cameras, have gained significant attention in recent years due to their high temporal resolution, high dynamic

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation

arXiv:2608.04333v1 Announce Type: new Abstract: Large language model (LLM) configuration evaluation is challenging due to limited evaluation budgets, varying costs, and multiple competing objectives.

Curiosity-Diffuser: Curiosity Guide Diffusion Models for Reliability

arXiv:2503.14833v2 Announce Type: replace-cross Abstract: One of the bottlenecks in robotic intelligence is the instability of neural network models. This leads to risks when applying intelligence in

safetyarxiv-cs-ai

DataRx: Missingness-Aware Sampling for Safer Large Language Model Task-Specific Fine-Tuning

arXiv:2608.04322v1 Announce Type: new Abstract: Task-specific fine-tuning can improve the performance of large language models (LLMs) on downstream tasks. However, our study reveals that task-specific

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Easy to Complete, Hard to Choose: Investigating LLM Performance on the ProverbIT Benchmark

arXiv:2608.04670v1 Announce Type: cross Abstract: Large Language Models (LLMs) have transformed computational linguistics and achieved remarkable performance across numerous natural language processin

Agents

Embedding Large Language Models into Flow Controls: An Agentic Framework for Adaptive and Trustworthy Automated Cooking

arXiv:2608.04768v1 Announce Type: new Abstract: Automated cooking robots have traditionally relied on predefined procedures and rule-based control, ensuring stable execution but offering limited perso

agentsarxiv-cs-cv

Enabling Urgency-aware Robot Swarm Intralogistics using Smart IoT Tags

arXiv:2608.04721v1 Announce Type: new Abstract: Warehouse items differ in how urgently they must be moved: perishable goods, pharmaceutical shipments, and just-in-time production materials must be del

safetyarxiv-cs-ro

EndoVLM: An Endoscopy Vision-Language Pre-training Model via Anatomy-Guided Sparsity and Progressive Alignment

arXiv:2608.04472v1 Announce Type: cross Abstract: The development of foundation models (FMs) is crucial for advancing endoscopic image analysis. However, existing endoscopy FMs mainly rely on self-sup

safetyarxiv-cs-ai

Agents

EviGraph: Evidence-Guided Autonomous Research Agents

arXiv:2608.04738v1 Announce Type: new Abstract: Autonomous research agents can generate hypotheses, execute experiments, and draft manuscripts, yet their outputs often contain unsupported claims and i

agentsarxiv-cs-ai

FBID: Adaptive Personalized Federated Learning for Robust Out-of-Distribution Attack Detection in IoT Networks

arXiv:2608.04073v1 Announce Type: cross Abstract: Personalized Federated Learning (PFL) has emerged as a promising solution for intrusion detection in heterogeneous IoT environments, as it can improve

Feasibility of Embedded Photoplethysmography Sensing in Short-Duration Tactile Interactions With Pocket-Sized Robots Using IMU- and Confidence-Based Filtering

arXiv:2608.04242v1 Announce Type: new Abstract: Ubiquitous companion robots offer a promising avenue for immediate anxiety relief in children, yet their effectiveness relies on the ability to monitor

researcharxiv-cs-ro

Feedback Loops and Code Perturbations in LLM-based Software Engineering: A Case Study on a C-to-Rust Translation System

arXiv:2512.02567v2 Announce Type: replace-cross Abstract: The advent of strong generative AI has a considerable impact on various software engineering tasks such as code repair, test generation, or la

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FinRpt: Dataset, Evaluation System and LLM-based Multi-agent Framework for Equity Research Report Generation

arXiv:2511.07322v3 Announce Type: replace-cross Abstract: While LLMs have shown great success in financial tasks like stock prediction and question answering, their application in fully automating Equ

Formal Analysis and Supply Chain Security for Agentic AI Skills

arXiv:2603.00195v2 Announce Type: replace-cross Abstract: 32 pages, 5 theorems with full proofs, 68 references, open-source tool: https://github.com/qualixar/skillfortify. v2: corrects the bibliograph

From Score Matrices to Football-Aware Match-State Simulation: An Auditable LLM Harness for Exact-Score Reranking

arXiv:2608.05030v1 Announce Type: new Abstract: Football score forecasting combines a strong statistical core with a difficult contextual edge. Dynamic Poisson-family models estimate team strength, ex

Galaxy Phase-Space and Field-Level Cosmology: The Strength of Semi-Analytic Models

model-releasesarxiv-cs-lg

arXiv:2512.10222v2 Announce Type: replace-cross Abstract: Semi-analytic models are a widely used approach to simulate galaxy properties within a cosmological framework, relying on simplified yet physi

Applications

Hardware Design and Security in the Era of Chiplets and LLMs

arXiv:2608.05063v1 Announce Type: cross Abstract: The semiconductor industry is undergoing a dual revolution: the shift toward heterogeneous 2.5D chiplet systems and the integration of Large Language

applicationsarxiv-cs-ai

HiSC: Hierarchical Spatial Clustering Token Compression for Efficient 3D Scene Understanding

arXiv:2608.04610v1 Announce Type: new Abstract: 3D vision-language models (3D VLMs) enable spatial reasoning over multi-view scenes but suffer from substantial token redundancy due to duplicated obser

researcharxiv-cs-cv

Leak-Resistant Unlearning: A New Benchmark for Evaluating Multi-Hop Reasoning Consistency and Recovery Robustness

arXiv:2608.04519v1 Announce Type: new Abstract: Benchmarking machine unlearning methods is critical to understand whether sensitive knowledge is removed from large language models (LLMs) or not. Curre

Local Ai

Leveraging Interpretable Tsetlin Machine for PDF Malware Detection

arXiv:2607.09290v2 Announce Type: replace-cross Abstract: In the digital era, Portable Document Format (PDF) is one of the most widely used file formats for storing and exchanging digital documents du

local-aiarxiv-cs-lg

LLM-based Vulnerability Discovery in Business Process Documentation

arXiv:2608.04271v1 Announce Type: cross Abstract: Just like software and hardware, business processes are susceptible to vulnerabilities that can lead to product quality issues, delays, and increased

researcharxiv-cs-cl

Manipulation-Proof Oblivious Audits against Deceptive Model Providers

arXiv:2608.04365v1 Announce Type: new Abstract: Audits have emerged as a critical instrument for algorithmic governance, providing a mechanism for external scrutiny and governance of machine learning

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MOAT: Model-Agnostic Randomized Transformations for preventing Efficiency Degradation Attacks on ViTs

arXiv:2608.04680v1 Announce Type: cross Abstract: To adopt the Vision Transformers (ViTs) in resource-constrained environment, token pruning is widely used to reduce computational cost without impacti

researcharxiv-cs-cv

Monte Carlo Tree Search for Table-to-Multimodal Report Generation

arXiv:2608.04071v1 Announce Type: new Abstract: Automatically generating professional multimodal reports comprising both textual analysis and visual charts from structured tabular data is a critical c

Multicalibration Yields Better Matchings

arXiv:2511.11413v2 Announce Type: replace Abstract: Consider the problem of finding the best matching in a weighted graph where we only have access to predictions of the actual stochastic weights, bas

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On the Effectiveness of Adaptation Strategies for VLM-Based Federated Learning in Remote Sensing

arXiv:2608.04791v1 Announce Type: new Abstract: Federated learning (FL) enables collaborative training of deep learning models across decentralized image archives without requiring data centralization

On The Suitability of Differential Dataflow For Datalog Interpretation In Highly Dynamic Settings

arXiv:2308.04214v2 Announce Type: replace-cross Abstract: In the domain of knowledge representation and reasoning within AI, datalog engines play an ever-increasingly crucial role. The crux of their o

One Surrogate to Fool Them All: Universal, Transferable, and Targeted Adversarial Attacks with CLIP

model-releasesarxiv-cs-lg

arXiv:2505.19840v3 Announce Type: replace-cross Abstract: Deep Neural Networks (DNNs) have achieved widespread success yet remain prone to adversarial attacks. Typically, such attacks either involve f

OutLangSplat: 3D Language Gaussian Splatting for UAV Outdoor Scenes

arXiv:2608.04560v1 Announce Type: new Abstract: 3D Language Gaussian Splatting embeds open-vocabulary language features into 3D Gaussian Splatting, providing an efficient explicit representation for t

safetyarxiv-cs-cv

Poly-OPD: Heterogeneous Multi-Teacher On-Policy Distillation for Capability-Selectable Flow Models

arXiv:2608.04349v1 Announce Type: new Abstract: Leading open text-to-image models often carry complementary strengths: one may lead on preference-aligned aesthetics while another follows compositional

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Local Ai

Promptable Animal Pose Tracking Across Species

arXiv:2608.04995v1 Announce Type: new Abstract: Animal pose estimation and tracking is important for wildlife monitoring and conservation research, and with limited expert time for labelling automated

local-aiarxiv-cs-cv

Reading Between the Frames: Interpreting Implicit and Non-literal Meaning in Social Media Videos

model-releasesarxiv-cs-cl

arXiv:2608.04939v1 Announce Type: new Abstract: Social media videos often communicate meanings that go beyond their visible actions, captions, or speech. A mundane clip may become humorous, ironic, or

Agents

ReCodeAgent: A Multi-agent Workflow for Language-Agnostic Translation and Validation of Large-Scale Repositories

arXiv:2604.07341v2 Announce Type: replace-cross Abstract: Most repository-level code translation and validation techniques have been evaluated on a single source-target programming language (PL) pair,

agentsarxiv-cs-lg

RepairFormer: Automated Repair of Structured Inputs Using Transformers

arXiv:2608.05060v1 Announce Type: cross Abstract: Structured input files such as JSON, DOT, OBJ, INI, S-expression, and TinyC are widely used in software systems, but small corruptions can cause parse

Local Ai

Risk Is Not the Target: A Monotonic Framework for Evaluating Wildfire Operational Risk Signals

arXiv:2607.21597v2 Announce Type: replace Abstract: Evaluating wildfire risk systems using standard machine-learning metrics such as F1-score or IoU is fundamentally flawed: these metrics assess event

local-aiarxiv-cs-ai

Searching for Sound-Meaning Collisions: Graph-Based Affordance Retrieval and Multi-Evaluator Ranking for Pun Translation at CLEF 2026 JOKER Task 2

arXiv:2608.04299v1 Announce Type: new Abstract: Fifteen years ago, Low proposed that pun translators should stop searching for equivalent words and instead search for new points of contact between sou

researcharxiv-cs-cl

Semantic Frame Interpolation

arXiv:2507.05173v2 Announce Type: replace Abstract: Generating intermediate video content of varying lengths based on given first and last frames, along with text prompt information, offers significan

SmartMage: Dynamic Modality Orchestration for 3D Scene Understanding

arXiv:2608.05137v1 Announce Type: new Abstract: Understanding 3D scenes is fundamental to embodied intelligence, requiring joint reasoning over heterogeneous information from multiple modalities, incl

Spend Bits Where Queries Look: KV Cache Vector Quantization with Attention-Preserving Transforms

arXiv:2608.04074v1 Announce Type: cross Abstract: Long-context LLM decoding reads the key-value (KV) cache at every step. Loading it takes longer than computing attention over it, so throughput is ban

SpikingNav: Robust Embodied Navigation with Spiking Neural Policies

arXiv:2608.05078v1 Announce Type: new Abstract: Embodied navigation requires an agent to make sequential decisions from egocentric observations in a physical environment. Existing Artificial Neural Ne

safetyarxiv-cs-ro

Stable Density Ridges: Consistency and Convergence of Subspace Constrained Mean Shift

arXiv:2608.05112v1 Announce Type: cross Abstract: The Subspace Constrained Mean Shift (SCMS) algorithm is a popular nonparametric method for extracting density ridges, which serve as a low-dimensional

Static Timing Orchestration for Tree-Structured Robot Control Firmware

arXiv:2608.04600v1 Announce Type: new Abstract: As robotic systems become increasingly complex, generating control firmware from structural description files has emerged as a promising paradigm for re

researcharxiv-cs-ro

Statistical learning theory and Occam's razor: Regularization

arXiv:2608.04049v1 Announce Type: cross Abstract: The principle of Occam's razor, which instructs us to prefer simplicity in inductive inference, has attracted much scrutiny both in the philosophy of