Search: “framework”

Trained Agentic Context Management

model-releasesarxiv-cs-cl

arXiv:2610.02404v1 Announce Type: cross Abstract: We study long context language models. Instead of training long context natively, or designing a long context harness, we train a model over the simpl

Uncovering EEG Patterns Consistently Associated with Cybersickness Discomfort Using Deep Learning Interpretability Maps

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DGX agent

arXiv:2512.20620v3 Announce Type: replace-cross Abstract: Uncomfortable sensations similar to motion sickness, called cybersickness, can develop when using Virtual Reality (VR) head-mounted displays.

researcharxiv-cs-lg

5 Oct 2026

Tutorials

Validated Data Onboarding for AI Demand Forecasting on U.S. Building Meter Data: Design, Controlled Evaluation, and a Corrected Negative Result

arXiv:2610.02397v1 Announce Type: new Abstract: Electric utilities and grid operators increasingly rely on machine-learning models to forecast next-day demand, and those models learn from meter data t

tutorialsarxiv-cs-lg

VisionMX: Unlocking Microscaling Post-Training Quantization for Vision Models

arXiv:2610.03218v1 Announce Type: new Abstract: Microscaling (MX) formats are emerging as a hardware-supported approach to efficient training and inference. They combine low-precision elements with sh

safetyarxiv-cs-cv

When Is Accuracy Evidence? A Unified Theory of Generalisation, Validation, and Information Fusion

arXiv:2610.03465v1 Announce Type: cross Abstract: K-fold cross-validation (CV) is widely used as evidence of out-of-sample performance, although folds are neither independent experiments nor equally i

Local Ai

Writerslogic at PAN 2026: Process over Content for Robust Detection under Domain Shift

arXiv:2610.03565v1 Announce Type: new Abstract: We describe the Writerslogic systems for three PAN at CLEF 2026 shared tasks (Reasoning Trajectory Detection, Voight-Kampff Generative AI Detection, and

local-aiarxiv-cs-cl

Applications

4Director: Controlling Video World Models with Rigid 3D Geometry

arXiv:2610.02160v1 Announce Type: new Abstract: Precise control over camera and object motion is essential for professional video production. Existing methods control objects only coarsely, through im

applicationsarxiv-cs-cv

A First Glance at Jev for Network Traffic Classification: Accuracy, Processing Time, and Cost

model-releasesarxiv-cs-lg

arXiv:2610.00376v1 Announce Type: new Abstract: We evaluate Jev on ten dataset-defined application labels in CESNET-QUICEXT-25 using only the first ten packets' sizes, directions, and inter-packet tim

Applications

A Hybrid Approach to Malware Detection: Integrating Few-Shot Model-Agnostic Meta-Learning with Autoencoders

arXiv:2610.01949v1 Announce Type: cross Abstract: Ransomware has emerged as a major cybersecurity threat, with incidents increasing in frequency and impact across critical sectors. These attacks are t

applicationsarxiv-cs-ai

A rubric landscape for evaluating clinical reasoning in large language models: what exists, what is missing, and what needs to be combined

arXiv:2610.01938v1 Announce Type: cross Abstract: Exam-style accuracy does not establish whether large language models (LLMs) reason well over clinical records. We define clinical reasoning as integra

safetyarxiv-cs-ai

Admissibility-Preserving Control for Multi-Input Systems with Joint Capacity Constraints

arXiv:2610.00533v1 Announce Type: cross Abstract: This paper addresses the control of multi-input strict-feedback nonlinear systems subject to a joint capacity constraint, in which the admissible inpu

researcharxiv-cs-ro

Agent Evaluation Reliability: More Tasks Won't (Always) Fix An Agent Leaderboard

arXiv:2610.00651v1 Announce Type: new Abstract: Agent evaluations are increasingly used to compare LLMs and inform deployment decisions, yet ranks can reflect not only the model but also the effects o

Are AI Coders Snitches? An Empirical Study of Pretraining Data Detection on Code Large Language Models

arXiv:2507.17389v2 Announce Type: replace-cross Abstract: Recent advances in code large language models (CodeLLMs) have made them indispensable tools in modern software engineering. However, these mod

Atoms to Processes: The Role of Artificial Intelligence and Machine Learning in Chemical Engineering

arXiv:2610.02014v1 Announce Type: new Abstract: The rapid maturation of artificial intelligence (AI) and machine learning (ML) has catalyzed a profound shift in how chemical engineering problems are f

agentsarxiv-cs-ai

Auto-Formalizing Neuro-Symbolic Predictors

arXiv:2610.01519v1 Announce Type: cross Abstract: Neuro-Symbolic (NeSy) predictors incorporate prior knowledge into the prediction process of neural networks, ensuring that outputs satisfy specified c

Beyond Diagonal State Space Models: Exact Non-Abelian Group Tracking, Solvability Barriers, and Geometric Physical Manifolds

arXiv:2610.00329v1 Announce Type: new Abstract: Selective state space models (SSMs), such as Mamba, S4D, and LRU, are bounded by transition matrix commutativity (A_t A_t' = A_t' A_t) and solvable affi

Beyond Final Accuracy: Auditing Communication in LLM Multi-Agent Systems

arXiv:2610.01042v1 Announce Type: new Abstract: Multi-agent communication aims to help agents benefit from one another's information. Yet improvements in system performance leave a fundamental ambigui

safetyarxiv-cs-ai

Beyond Leaderboard Scores: A Deployment-Focused Protocol for Interpretable Tracking Evaluation in Pedestrian-Centric Environments

arXiv:2610.01682v1 Announce Type: cross Abstract: Mobile robots operating among pedestrians need trajectories that become available quickly, remain spatially credible through missed observations, pres

Beyond Pointwise Error: A Multi-Metric Evaluation of Spatial Climate Downscaling

arXiv:2610.01579v1 Announce Type: cross Abstract: Climate downscaling aims to reconstruct fine scale spatial fields from coarse resolution inputs. Evaluating the quality of these reconstructions is ch

Can AI Scientists Coordinate at Runtime?

arXiv:2610.00980v1 Announce Type: cross Abstract: Multi-agent AI scientists have shown improving performance across a diverse range of tasks. Yet a common approach is design-time agentic orchestration

agentsarxiv-cs-ai

CAVE-Mem: Boundary-Aware Experience Validation for Memory Search

arXiv:2610.00238v1 Announce Type: cross Abstract: Long-term memory agents increasingly rely on it- erative search and reusable experience to answer questions over large personal, factual, or narrative

researcharxiv-cs-ai

Context-Aware Error Mitigation Orchestration for Hybrid Quantum Reinforcement Learning on NISQ Systems

arXiv:2610.01253v1 Announce Type: new Abstract: Quantum Reinforcement Learning (QRL) integrates reinforcement learning with parameterized quantum circuits and is a promising approach to combinatorial

safetyarxiv-cs-lg

Contingent Exposure Routing for Financial AI: Outage Risk and the Cost of Indivisible Decisions

arXiv:2610.00239v1 Announce Type: new Abstract: Model failover restores availability, but changes which financial institutions share decision errors. We formulate outage-contingent routing through a l

agentsarxiv-cs-lg

Continuous Process-Level Evaluation for Evolving Enterprise AI Agent Skills

arXiv:2610.01833v1 Announce Type: new Abstract: Enterprise AI agent skills evolve as tool APIs, models, and specifications change, yet final-output evaluation can miss process-level behavioral drift.

agentsarxiv-cs-ai

Controllable Multi-label Video Safety Detection via Adaptive Tversky Policy Optimization

arXiv:2610.02019v1 Announce Type: cross Abstract: The rapid growth of video-based social media has increased users' exposure to harmful content, creating a need for reliable automated video safety det

safetyarxiv-cs-cv

Decision Titan: Test-Time Training for Long-Term Memory in Offline Reinforcement Learning

arXiv:2610.01513v1 Announce Type: new Abstract: Long-term dependencies remain a major challenge for sequential decision-making in the field of AI: RNNs suffer from vanishing gradients and the limited

DiVid: Diagnosing Dimension-Specific Diversity Collapse in Video Generation Models

arXiv:2610.01661v1 Announce Type: new Abstract: Despite remarkable progress, video generation models often produce highly similar outputs when repeatedly sampled from the same prompt, limiting their u

Do MLLM Judges Judge the Edit? Auditing Bias in Image Editing Evaluation with Verified Quality Preservation

arXiv:2610.01670v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) are increasingly used as automated judges for instruction-based image editing and as reward signals for model t

DramaAgent: Agentic Storytelling Video Generation

arXiv:2610.00097v1 Announce Type: new Abstract: Recent diffusion and autoregressive models have substantially improved text-to-video generation, yet producing coherent long-form story videos with cons

agentsarxiv-cs-cv

Applications

Energy Time-Series Imputation with Differentially Private Diffusion Models via Clipping-Aware Objective Conditioning

arXiv:2610.00209v1 Announce Type: new Abstract: Reliable recovery of missing measurements is important for monitoring and analysis in energy time-series systems, where fine-grained measurements may co

applicationsarxiv-cs-lg

Every Ablation Is a Dose: Counterweights and the Semblance of Self-Repair

model-releasesarxiv-cs-lg

arXiv:2610.02173v1 Announce Type: new Abstract: Ablate a component of a language model, and other components often appear to adjust and compensate. This phenomenon, termed self-repair, has been observ

External Observers May See More Clearly: Cross-Model Span-Level Hallucination Detection in Large Language Models via Hidden State Probing

arXiv:2610.02066v1 Announce Type: new Abstract: As Large Language Models (LLMs) increasingly serve as foundational reasoning engines, their tendency to hallucinate remains a critical vulnerability. Wh

researcharxiv-cs-ai

Fault-Tolerant Budget Conservation in Distributed Multi-Agent Delegation

arXiv:2610.00349v1 Announce Type: new Abstract: Resource limits are becoming an authorization boundary for AI agents that delegate work across concurrent and failure-prone workers. Parent-child alloca

safetyarxiv-cs-ai

Faynt: Scaling and Optimizing Policies for Competitive Melee

model-releasesarxiv-cs-lg

arXiv:2610.02144v1 Announce Type: new Abstract: We introduce Faynt, a family of 10M- and 75M-parameter Transformer policies for Super Smash Bros. Melee, each controlling all 26 characters with a singl

FedCKA: Representation-Guided Layer Personalization for Federated 3D Perception Across Driving Domains

arXiv:2610.01510v1 Announce Type: new Abstract: Robust perception in intelligent vehicles demands 3D object detectors that remain dependable under domain shifts, such as changes in time of day, locati

Federated Learning for LLMs over Mobile Networks: Issues and Solutions in the RAN Transport

arXiv:2610.01304v1 Announce Type: cross Abstract: Federated LLM fine-tuning enables large models to be adapted using private and geographically distributed data at the network edge, creating recurring

FedFit: Federated Fine-Tuning of LLMs via Vector-Bank Parameterization and Quantization

arXiv:2610.01537v1 Announce Type: new Abstract: Federated Learning (FL) enables privacy-preserving fine-tuning of Large Language Models (LLMs), yet the massive communication overhead remains a critica

FiVOS: A Fish Segmentation Algorithm Based on Interactive Video Object Segmentation and Filter Enhancement

arXiv:2610.01480v1 Announce Type: new Abstract: With the continuous expansion of aquaculture, precise and efficient monitoring of fish behavior has become increasingly critical for improving farming e

researcharxiv-cs-cv

Fixing a Model That Learned Worse Cancer Means Lower Risk: Monotonic Constraints in Bladder Cancer Recurrence Prediction

arXiv:2610.00858v1 Announce Type: new Abstract: Background and Objective: Clinicians expect recurrence risk to climb with cancer severity. In a UK multicentre trial, an unconstrained XGBoost model lea

FlashDexRetarget: Accelerating Dexterous Manipulation Data Generation through Multi-Motion Retargeting

model-releasesarxiv-cs-ro

arXiv:2610.01849v1 Announce Type: new Abstract: Human hand-object demonstrations offer a reusable source of dexterous robot manipulation data, but transferring them across embodiments requires physica

FlashNav: Training Deployable Robot Navigation Policies in Seconds

model-releasesarxiv-cs-ro

arXiv:2606.15846v2 Announce Type: replace Abstract: Training Deep Reinforcement Learning (DRL) navigation policies for different robot configurations remains time-consuming. We present FlashNav, a GPU

Tutorials

Four Ways to Grow a Classifier and Why One of Them Cannot Learn

arXiv:2610.00180v1 Announce Type: cross Abstract: Constructive classifiers add structure while they train: a level to a tree, a unit to a hidden layer, a split at a leaf. This paper asks what each of

tutorialsarxiv-cs-ai

Local Ai

From Knowledge Access to Source Learning: Developing Source-Specific Competence

arXiv:2610.02150v1 Announce Type: cross Abstract: Large language model (LLM) agents increasingly rely on persistent external sources to solve sequences of knowledge-intensive tasks. Existing methods i

local-aiarxiv-cs-ai

Fully Online Decentralized Learning in Stochastic Games with Unknown Independent Chains

arXiv:2610.01181v1 Announce Type: new Abstract: We consider stochastic games with independent controlled chains and unknown transition kernels, where players observe only their local states and realiz

G2-Nav: Grounded and Guarded Vision-Language Costmaps for Robot Social Navigation

arXiv:2607.16956v2 Announce Type: replace Abstract: Social navigation requires the robot to reason and respond in complex real-world environments. While recent works attempt to incorporate human-level

safetyarxiv-cs-ro

GenGait: A Transformer-Based Model for Human Gait Anomaly Detection and Normative Twin Generation

arXiv:2604.01997v2 Announce Type: replace Abstract: Gait analysis provides an objective characterization of locomotor function and is widely used to support diagnosis and rehabilitation monitoring acr

researcharxiv-cs-ai

Local Ai

GLoC-EHR: Evidence-Cited Clinical Reasoning over Global Context and Local EHR Events

arXiv:2610.01076v1 Announce Type: new Abstract: Structured electronic health records (EHRs) contain a patient's clinical trajectory as a sequence of clinical codes. Answering clinical questions from s

local-aiarxiv-cs-lg

Have an LLM Write Your Anomaly Detector: Autonomous Discovery of Compact, Interpretable Detectors for Time Series

arXiv:2610.01223v1 Announce Type: cross Abstract: Time-series anomaly detection trades off predictive accuracy, computational efficiency, and interpretability. We use a large language model not as the