Search: “papers”

Geometry Conditioning in an Embodied SLM: Training Controls and Robustness Diagnostics in a 0.8B Hybrid Model

arXiv:2609.09213v1 Announce Type: new Abstract: We study how physical-state inputs affect a 0.8B hybrid language model adapted for manipulation with 6.2M trainable parameters. Six conditions are train

safetyarxiv-cs-ro

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IdeaAMBIG: Benchmarking Implementation-Critical Gaps in Research-Idea Specifications

DGX agent

arXiv:2609.10539v1 Announce Type: new Abstract: A research idea may be novel, coherent, and scientifically plausible, yet its proposed method may remain insufficiently specified for faithful implement

model-releasesarxiv-cs-cl

10 Sept 2026

IMU-Centric Moving Horizon Estimation for Lateral Dynamics Estimation Across Vehicles and Grip Conditions

model-releasesarxiv-cs-ro

arXiv:2609.10202v1 Announce Type: cross Abstract: Accurate estimation of lateral vehicle dynamics near the adhesion limit is important for stability control and high-performance driving, but lateral v

Integrated Prediction and Multi-period Portfolio Optimization

arXiv:2512.11273v3 Announce Type: replace-cross Abstract: Multi-period portfolio optimization is important for real portfolio management, as it accounts for transaction costs, path-dependent risks, an

Hardware

Interface-Aware KV Cache Quantization for Dense On-Chip NVM in Long-Context LLM Decoding

arXiv:2609.05764v1 Announce Type: cross Abstract: The key-value (KV) cache is the dominant memory bottleneck in long-context large language model (LLM) decoding: every step reads it entirely, so decod

hardwarearxiv-cs-ai

Interpreting Object-Dependent Concept Brittleness in Text-to-Image Diffusion Models

arXiv:2609.09909v1 Announce Type: new Abstract: Although text-to-image diffusion models generally exhibit strong prompt-following ability, we identify a persistent and previously underexplored failure

researcharxiv-cs-cv

Learning with Synthetic Data via SGD in High-Dimensional Linear Regression

arXiv:2609.09572v1 Announce Type: cross Abstract: Synthetic data has become a promising way to scale model training beyond limited human-generated data but it may also induce strong model collapse (Do

safetyarxiv-cs-lg

LiteRAG: Cost-Efficient Graph-Based Retrieval-Augmented Generation

arXiv:2609.10239v1 Announce Type: cross Abstract: Graph-based retrieval can improve multi-hop question answering, but existing approaches often incur high query-time costs and produce diffuse, oversiz

Local Ai

Maverick: Private and Verifiable LLM Inference Made Practical via Matrix-Vector Multiplication Delegation

arXiv:2609.10264v1 Announce Type: cross Abstract: Open-source large language models (LLMs) are increasingly competitive with closed-source models while offering transparency and the ability to run inf

local-aiarxiv-cs-lg

MiNCE: Nonparametric, Strongly Consistent Confidence Envelopes for Band-Limited Functions and their Smoothed Spectra

arXiv:2609.09436v1 Announce Type: cross Abstract: Minimum-norm confidence envelope strategies offer a nonparametric approach to constructing nonasymptotic, simultaneous confidence regions for band-lim

MLLMs Hallucinate when Information Distribution Drifts in Synergy Heads

arXiv:2609.09206v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) often struggle with hallucinations, thus hindering their reliable practical applications. Existing attention-

researcharxiv-cs-cl

Multi-Functional Embedding Models for Funder Name Disambiguation in Scientific Publication Records

arXiv:2609.09984v1 Announce Type: new Abstract: Understanding the historical allocation and distribution of research funding advances our knowledge of how scientific research is supported across field

On-Policy Distillation for Vision-Language Model Adaptation, an Effective Paradigm on Low-Quality Multimodal Data

arXiv:2609.10321v1 Announce Type: new Abstract: Knowledge distillation offers an efficient route to transfer a task-adapted vision-language teacher to a compact student. The training target in current

safetyarxiv-cs-cl

On Scaling Coordinate-Based Neuroevolution: The Quadtree Bottleneck in ES-HyperNEAT

model-releasesarxiv-cs-lg

arXiv:2608.24480v1 Announce Type: cross Abstract: ES-HyperNEAT evolves substrate topology through adaptive quadtree subdivision; to our knowledge, no implementation with full population-level GPU para

Agents

Online Inverse Integer Linear Optimization via Small-Gradient Skipping: Constant Regret and Finite Mistakes

arXiv:2609.09809v1 Announce Type: new Abstract: In online inverse linear optimization, the learner predicts a weight at each round, observes the optimal action of the agent, and updates its prediction

agentsarxiv-cs-lg

Open Tabular Insight Extraction: Where Do We Stand, and Where Should We Go?

arXiv:2609.07629v1 Announce Type: cross Abstract: Democratizing access to the knowledge held in large corpora of tables such as data lakes is emerging as a central research challenge. Research in this

Personalized Execution Time Optimization for Billion-Scale Scheduled Jobs

arXiv:2203.06158v3 Announce Type: replace Abstract: Scheduled batch jobs are widely used on asynchronous computing platforms to execute enterprise applications such as promotional notifications and ca

safetyarxiv-cs-lg

Physics-informed neural networks by Gradient-Guided Gaussian Adaptive Sampling (3GAS-PINNs)

model-releasesarxiv-cs-lg

arXiv:2609.09162v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) provide a mesh-free framework for solving partial differential equations, yet their performance in nonlinear pr

ProcArena: A Multi-Scenario Benchmark for LLMs on Direct and Interactive PL/SQL Development from Natural Language

arXiv:2609.06527v1 Announce Type: cross Abstract: Large language models (LLMs) have shown strong potential for translating natural-language (NL) requirements into PL/SQL programs, attracting increasin

Applications

Quantile-Led Feature Extraction for Multi-Horizon Predictive Maintenance in Industrial Manufacturing Systems

arXiv:2609.07533v1 Announce Type: new Abstract: In data-driven predictive maintenance (PdM), feature extraction is usually treated as fixed preprocessing: a descriptor set is chosen once and reused wh

applicationsarxiv-cs-ai

RAP: Research Attention Prediction Reveals Target-Conditioned Evidence Acquisition Biases

arXiv:2609.10092v1 Announce Type: cross Abstract: Large language models (LLMs) increasingly act as research agents, yet their ability to track shifts in research attention is difficult to evaluate bec

Revoked but Still Authoritative: An Empirical Study of Revocation Enforcement in Agent-Memory Systems

arXiv:2609.08258v1 Announce Type: new Abstract: Long-running language-model agents depend on persistent memory. Many agent-memory systems preserve history through soft revocation: a contradicted fact

safetyarxiv-cs-ai

Applications

Robust Beam Prediction for V2X Networks with Multi-Modal Sensing

arXiv:2609.10200v1 Announce Type: new Abstract: Integrated sensing and communication (ISAC) provides a promising foundation for beam prediction in future vehicle-to-everything (V2X) networks. However,

applicationsarxiv-cs-lg

S^3-Bench: Evaluating Speech Interaction Models as Scientific Voice Assistants

arXiv:2609.09852v1 Announce Type: new Abstract: The advance of multimodal large language models (MLLMs) has fundamentally reshaped the paradigm of human-computer interaction, especially speech interac

researcharxiv-cs-cl

Local Ai

SCCM : Stream Cruise Control Method for Automated Drift Detection and Adaptation

arXiv:2609.09432v1 Announce Type: new Abstract: Real-world datasets often exhibit evolving distributions, known as concept drift. Ignoring drift degrades predictive performance, while reliance on fixe

local-aiarxiv-cs-lg

SciLitBench: Benchmark and Design Principles for LLM-Powered Systematic Literature Reviews

arXiv:2609.05505v1 Announce Type: new Abstract: Systematic reviews require sustained human judgment across thousands of records, yet existing evaluations of large language models (LLMs) typically exam

Scratchy: Visual-Scratchpad Multimodal Reasoning for Cryptographic Proof Generation in EasyCrypt

arXiv:2609.06226v1 Announce Type: cross Abstract: Large language models (LLMs) have recently made substantial progress in formal proof generation, yet presenting distinctive challenges in cryptographi

Searching for New Physics with Reinforcement Learning

arXiv:2609.10382v1 Announce Type: cross Abstract: Finding new physics (NP) is the most important problem in particle physics today. Studying ``anomalies'', i.e., measurements of low-energy observables

SerenAI: State-transition system inspired by text-based world AI models

arXiv:2609.06647v1 Announce Type: new Abstract: Although professional workflows leverage large language models widely, the interpretation for auditing unconstrained free-text generation is usually int

Shape-guided Gaussian Splatting for Sparse-View X-ray 3D Reconstruction

arXiv:2609.10376v1 Announce Type: new Abstract: Sparse-view X-ray 3D reconstruction is essential for reducing radiation exposure, but recovering a density field from a handful of X-ray projections is

researcharxiv-cs-cv

Simulating the Marginal Green Contribution of AI Modules in a Smart-Agriculture Platform: Evidence from Two Monte Carlo Experiments

arXiv:2609.06740v1 Announce Type: new Abstract: Smart agriculture platforms usually bundle AI diagnosis, IoT sensing and decision push into a single package, so the green benefit attributable to each

Staying on the Attack Path: Structured State for Long-Horizon Automated Penetration Testing

arXiv:2609.07344v1 Announce Type: cross Abstract: Large language model (LLM) based agents are increasingly applied to cybersecurity tasks such as vulnerability discovery and automated penetration test

🌐 Supporting open source. Expanding deployment options. We’ll work closely with the open-source community on V4.1-Flash inference support a…

model-releasesdeepseek--x

🌐 Supporting open source. Expanding deployment options. We’ll work closely with the open-source community on V4.1-Flash inference support and explore more deployment options. Planning a large-scale de

Symbolic Informalization: Fluent, Productive, Multilingual

arXiv:2606.16893v2 Announce Type: replace Abstract: Symbolic informalization enables a reliable conversion of formal mathematics to natural language. It has the potential to make machine-checked conte

Agents

The End of AI Exponentiation: Fluttering Inside and Outside AI Bubble

arXiv:2609.05894v1 Announce Type: new Abstract: The exponentiation of Artificial intelligence (AI) in the recent past has entered a transformative era that has been driven by the growth in large langu

agentsarxiv-cs-ai

Applications

Theoretical Analysis of Measure Consistency Regularization for Partially Observed Data

arXiv:2602.01437v2 Announce Type: replace Abstract: The problem of corrupted data, missing features, or missing modalities continues to plague the modern machine learning landscape. To address this is

applicationsarxiv-cs-lg

TIDE: Trustworthy and Interpretable Battery Degradation Estimation with Contextual Learning and Symbolic Distillation

arXiv:2607.14640v2 Announce Type: replace Abstract: Battery health estimation is fundamental for battery management in battery-powered systems, where inaccurate health states may affect control, maint

Towards a Resilience-Theoretic Foundation for Adversarial Robustness in Industrial Control System Anomaly Detection

arXiv:2609.07244v1 Announce Type: cross Abstract: Anomaly-based intrusion detection systems in industrial control systems (ICS) and operational technology (OT) environments are increasingly required t

Typed Federated Artifacts for the Agentic Web:Sharing Tool-Routing Knowledge Across Frozen,Heterogeneous LLM Agents

arXiv:2609.06815v1 Announce Type: cross Abstract: An open, networked web will allow agents to run frozen models from multiple vendors, keep their history private, and teach each other which tool to ca

Uncertainty-Aware Sea-Ice Type Mapping with Multiple Ice Charts

arXiv:2609.09451v1 Announce Type: new Abstract: Sea-ice stage of development (SoD) describes the age and associated thickness of sea ice and provides important information for navigation, and operatio

Unveiling Hidden Threats: Using Fractal Triggers to Boost Stealthiness of Distributed Backdoor Attacks in Federated Learning

arXiv:2511.09252v2 Announce Type: replace-cross Abstract: Traditional distributed backdoor attacks (DBA) in federated learning improve stealthiness by decomposing global triggers into sub-triggers, wh

WAPP: Safe Learning of Positive Security WAF Policies from Live Traffic

arXiv:2609.06840v1 Announce Type: cross Abstract: Web Application Firewalls (WAFs) mainly rely on signatures to detect known attacks, which can leave gaps against modified or previously unseen payload

safetyarxiv-cs-ai

We Built a Mirror and Mistook It for a Mind: Causal Liability and the Fallacy of AI Consciousness

arXiv:2609.06715v1 Announce Type: new Abstract: The contemporary debate over machine consciousness begins from a concealed assumption: that the object called 'AI' already constitutes the kind of entit

When Auditors Fabricate: Batch-Size Degradation and Confident Hallucination in LLM Detection of Planted Document Contamination

arXiv:2609.09696v1 Announce Type: new Abstract: Large language models are increasingly proposed as automated auditors of document quality, yet their reliability as detectors of planted errors is poorl

When Intelligence Becomes Agency: A Theory of Governed, Proactive Agency for Symbiotic AI Systems

arXiv:2609.07741v1 Announce Type: new Abstract: Persistent AI assistants are intended to extend human attention, memory, and coordination across changing digital and physical environments. To be truly

Why Is Video Still So Expensive? A Survey of Inference-Efficiency Mechanisms in Video and Audiovisual LLMs

arXiv:2609.10355v1 Announce Type: cross Abstract: Video understanding has rapidly evolved toward video large language models (VideoLLMs): systems that couple video representations with pretrained larg

World-Time Compute with Verified Code World Models

arXiv:2609.09163v1 Announce Type: new Abstract: LLMs generalize across a domain only after seeing many real, labeled examples, which most domains lack. We study a way to manufacture it cheaply. When a

Local Ai

A Cloud-Based Hybrid Model for Real-Time Detection of BRTA-Approved Licence Plates Using YOLO Tiny and Haar Cascade