Search: “models”

Learning to Simulate Individuals from Macro Social Signals

arXiv:2610.07062v1 Announce Type: cross Abstract: Large language models are increasingly used to simulate how individuals respond to new situations, yet the behavioral reasoning behind these responses

safetyarxiv-cs-ai

Logbook: Extremely Long-form Audio Event Understanding

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DGX agent

arXiv:2610.07338v1 Announce Type: cross Abstract: Audio benchmarks are built around short, pre-segmented clips, limiting model design to brief inputs or fixed vocabularies. To close this gap, we intro

model-releasesarxiv-cs-ai

7 Oct 2026

Machine Learning for German Redispatch Forecasting under Data Delays and Temporal Distribution Shift

arXiv:2610.08337v1 Announce Type: cross Abstract: Public redispatch records provide empirical data for grid congestion forecasting, but delayed reporting, zero-inflated distributions, and temporal shi

MedZERO: Self-Evolving Agents for Open-Ended Medical Reasoning Through Controlled Knowledge Accumulation

arXiv:2610.08327v1 Announce Type: new Abstract: Large language models (LLMs) have shown promise in medical question answering and clinical reasoning, yet their improvement remains constrained by stati

researcharxiv-cs-ai

MemFLoRA: Memory-Floor LoRA for CNN Adaptation at the Edge

arXiv:2610.08669v1 Announce Type: cross Abstract: On-device learning is necessary when the model encounters user-,sensor-, or environment-specific shifts after deployment. Although parameter-efficient

Multi-Label Perceptual Bug Detection in Video Games using Deep Learning on Gameplay Footage

arXiv:2610.08593v1 Announce Type: new Abstract: Traditional approaches for automated bug detection in video games, such as manual testing, can be beneficial for the improvement of quality assurance, b

No Transformer Beats Six Covariates: Long-Horizon Prediction of Depressive Symptoms from Childhood Essays

arXiv:2610.07764v1 Announce Type: cross Abstract: Natural language processing (NLP) models can detect depression-related language in text written near the time symptoms are measured, but whether pretr

researcharxiv-cs-ai

Privileged Context as Drift in On-Policy Self-Distillation

arXiv:2610.07842v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) trains a language model to match a copy of itself conditioned on privileged context. Existing work varies what privil

RADC: Risk-Aware Dual Caching for Vision-Language Test-Time Adaptation

arXiv:2610.06932v1 Announce Type: new Abstract: Cache-based test-time adaptation (TTA) for vision-language models is often hindered by background bias in global representations and unreliable entropy-

safetyarxiv-cs-cv

SAE++: Cascaded Sparse Autoencoders Learn Multi-Level Visual Concepts in Multimodal LLMs

arXiv:2606.16193v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) have demonstrated strong performance on vision-language tasks, yet their internal visual representati

SSR: Sparse Segment Reduction for Ternary GEMM Acceleration

arXiv:2610.08403v1 Announce Type: new Abstract: Large Language Models (LLMs) require substantial computational resources, limiting their deployment on resource-constrained hardware. Ternary LLMs mitig

TARE: Weigh a Never-Poisoned Twin Before Reading Backdoor-Defense Costs

arXiv:2610.06994v1 Announce Type: cross Abstract: Backdoor-defense leaderboards print a clean-accuracy drop and read it as removal cost. Measured on the poisoned victim alone, the drop cannot separate

Targeted search shows that random-device testing underestimates worst-case error in a simulated wave-based neural operator

arXiv:2610.07529v1 Announce Type: new Abstract: Wave-based processors promise fast, energy-efficient Fourier layers for neural operators. They are usually validated on randomly sampled devices, but us

safetyarxiv-cs-lg

Too Categorical to be Human: Emotion Concepts in LLMs and Humans

arXiv:2508.05880v3 Announce Type: replace-cross Abstract: Understanding human emotions is central to user-facing AI applications, safety alignment, and the simulation of human behavior. As emotional s

Uncertainty in Representation Learning on Knowledge Graphs

arXiv:2610.06974v1 Announce Type: new Abstract: Knowledge graph embedding (KGE) methods represent entities and predicates in continuous vector spaces to infer missing knowledge. Despite strong benchma

UniCounting: Instance-Aware Proposal Consolidation for Image-Query-Free Multi-Category Counting

arXiv:2610.08379v1 Announce Type: new Abstract: Visual counting is commonly formulated as counting a single specified target, with a model receiving an image-specific exemplar, text query, or target c

Verifying Coordination in Parallel Coding Agents: NP-Bench and a Scheduling Planner

arXiv:2610.07261v1 Announce Type: new Abstract: A team of coding agents can look fine agent by agent yet fail as a team: each passes its own tests while the merged result is broken, and single-agent e

Von Neumann Networks

arXiv:2605.05780v2 Announce Type: replace Abstract: In the mid-twentieth century, mathematician and polymath John von Neumann created a computational system on an array of cells as a simple model of t

Will the Judge Flip? Predicting Position-Sensitive LLM Judgments from Residual Stream Activations

arXiv:2610.07115v1 Announce Type: cross Abstract: The order in which candidate responses are presented can change an LLM judge's verdict. Detecting such a position flip ordinarily requires judging eac

WorldSonus: Bringing Sound to Worlds

arXiv:2610.08760v1 Announce Type: cross Abstract: Recent advances in world models have enabled increasingly realistic visual synthesis. However, these generated environments remain largely silent. Bri

safetyarxiv-cs-ai

AdaSpark: Adaptive DSpark with Online Learning for Tree Verification and N-gram Fill

arXiv:2610.05774v1 Announce Type: new Abstract: Block drafters such as DSpark propose ranked candidates for several positions in one forward pass, and a tree verifier checks them in one pass of the ta

AIProver: Agentic Auto-Formalization of Mathematical Research via Certificate-Driven Evolving Harness

arXiv:2610.05367v1 Announce Type: cross Abstract: Proof auto-formalization translates natural-language (NL) theorems and proofs into a formal language (FL) such as Lean, enabling mechanical verificati

Answer with Evidence: Consistency-Aware Grounded Visual Question Answering for Roadside Traffic Scenes

arXiv:2610.05274v1 Announce Type: new Abstract: Roadside traffic reasoning requires every free-form textual claim to be backed by visual evidence. Existing grounded multimodal large language models (M

Beyond Plausibility: Verifiable Fine-Grained Image Editing on Structured Assets

arXiv:2610.04381v1 Announce Type: new Abstract: Fine-grained image editing requires more than producing a visually plausible result: an editor must execute the requested attribute change precisely whi

Beyond Token Accuracy: Prioritizing What Matters for Visual Reconstruction

arXiv:2610.03822v1 Announce Type: new Abstract: Tokens have become a unified interface for multimodal foundation models, making visual-token communication a natural paradigm for efficient image delive

safetyarxiv-cs-cv

Beyond Transport Cost: Routing Differences between Flow Matching and Optimal Transport

arXiv:2610.05921v1 Announce Type: cross Abstract: In generative models, Optimal Transport (OT) is used to improve Flow Matching (FM) by reducing noise-data coupling cost. However, different noise-to-o

BridgeCast: Bridging Ocean Wave Forecasts to Reanalysis via Flow Matching with Exogenous Variables

arXiv:2610.03759v1 Announce Type: cross Abstract: Ocean wave forecasting is essential for maritime safety, offshore operations, and coastal resilience, yet remains challenging due to systematic biases

safetyarxiv-cs-lg

CASE: Cost-Aware Stopping for Efficient Long-Video Agents

arXiv:2610.05400v1 Announce Type: cross Abstract: Long-video agents can actively gather question-relevant evidence, but they typically leave a central decision implicit: when has the agent seen enough

CHAOSMINING: Benchmarking Post-Hoc Attribution with Sparse Informative Features in High Dimensions

arXiv:2406.12150v2 Announce Type: replace Abstract: Post-hoc attribution is widely used to identify important model inputs, but evaluating whether these attributions identify truly informative feature

COVER: Learning to Accept More in Selective Sleep Staging

arXiv:2610.03911v1 Announce Type: new Abstract: Traditional sleep-staging methods apply the same model to every EEG epoch. Such uniform deployment expends computation on epochs that a smaller model co

researcharxiv-cs-lg

EMBER-Bench: Benchmarking Cross-Event Causal Memory in Long-Horizon Embodied Tasks

arXiv:2610.05013v1 Announce Type: new Abstract: Lifelong physical agents must reason over extended interactions where past events continue to shape the world long after they disappear from view. Beyon

Agents

EvoCast: Reliable Autonomous Research Agents for Iterative Forecasting Architecture Evolution

arXiv:2610.04517v1 Announce Type: cross Abstract: Deep time-series forecasting models have rapidly diversified, yet adapting them to a specific task still requires extensive expert effort in model sel

agentsarxiv-cs-lg

Evolutionary feature selection for spiking neural network pattern classifiers

arXiv:2604.26654v1 Announce Type: cross Abstract: This paper presents an application of the biologically realistic JASTAP neural network model to classification tasks. The JASTAP neural network model

researcharxiv-cs-lg

FACET: Factorized Asymmetric Conditioning for Efficient Transport in High-Fidelity Fluorescence Microscopy Synthesis

arXiv:2610.05353v1 Announce Type: cross Abstract: Fluorescence microscopy reveals where proteins localize, but only a limited number of proteins can be imaged in the same cell; generating these images

Feature identification for parameter extraction and defect detection using machine learning

arXiv:2610.05812v1 Announce Type: new Abstract: Process control of advanced semiconductor nodes is not only pushing the limits of metrology equipment requirements in terms of resolution and throughput

Gauss-Map Variation for Image Denoising: Geometric Analysis and an Anderson--Accelerated Majorization--Minimization Method

arXiv:2610.05801v1 Announce Type: new Abstract: We propose a Gauss-map variation (GMV) model for image denoising that measures the spatial variation of the tangent-plane projectors of the scaled image

researcharxiv-cs-cv

Applications

GOTT: Object-centric Dexterous Manipulation with a Reusable Cross-Embodiment Primitive

arXiv:2610.03861v1 Announce Type: cross Abstract: Foundation models and large-scale human data provide rich sources of manipulation intent, but translating this intent into multi-fingered robot behavi

applicationsarxiv-cs-cv

Grounded in Time: A Multi-Source Dataset and Benchmark for Temporal Grounding in Robotic Manipulation

arXiv:2610.04255v1 Announce Type: cross Abstract: Robotic manipulation often requires inferring task-relevant states from past interactions when the current observation alone is insufficient to determ

Hamiltonian Metric Learning and Energy-Based Training: A Dissipative Geometric Framework for Optimization

arXiv:2610.04969v1 Announce Type: new Abstract: Optimization in machine learning is usually expressed through iterative rules that update model parameters using information from the loss landscape. In

Image resolution enhancement for advanced semiconductor nodes

arXiv:2610.05809v1 Announce Type: new Abstract: Advanced semiconductor nodes are pushing the limits of feature sizes and require metrology with sub-nm resolution without compromising on the throughput

LoRA's Second Descent Extends Beyond Parameter Parity

arXiv:2610.04507v1 Announce Type: new Abstract: Double descent has sparked considerable interest, with recent work relating it to the data, the model and the learning configuration. Practical fine-tun

MAGIC: Topology-Aware Analytic Graph Few-Shot Class-Incremental Learning

arXiv:2610.04963v1 Announce Type: new Abstract: Graph few-shot class-incremental learning (GFSCIL) requires a model to continually recognize emerging classes from only a few labeled nodes while preser

MTOR: Generalizable AI-Generated Video Detection with Multimodal Semantics and Temporal Over-Regularity

arXiv:2610.06378v1 Announce Type: new Abstract: The rapid evolution of video generation has narrowed the perceptual gap between authentic and synthetic videos, making generalizable AI-generated video

Neural Barriers: An Online Certifiable Learning-enhanced Adaptive High Order Safety Critical Control

arXiv:2610.05542v1 Announce Type: new Abstract: Control barrier functions are an effective model-based tool to formally certify the safety of a system. However, transferring their theoretical guarante

safetyarxiv-cs-ro

On Hyperparameter Tuning on the Test Set

arXiv:2610.05902v1 Announce Type: cross Abstract: 'Don't tune hyperparameters on the test set' is often stated in machine learning textbooks. Violating it is considered a cardinal sin that produces mi

OVAL: Output-Aware Local Page Bases for KV Cache Retrieval

arXiv:2610.06686v1 Announce Type: new Abstract: Long context inference with large language models becomes increasingly expensive as attention must operate over an ever growing KV cache. Page sparse at

P3: Persistent Particle Planning for Constrained Diffusion Control

arXiv:2610.06002v1 Announce Type: cross Abstract: Diffusion models provide expressive priors over trajectories, but adapting these priors to test-time constraints requires maintaining feasibility and

researcharxiv-cs-lg

Local Ai

Prompt and Refinement: Asymmetric Mutual Learning for Infrared Small Target Detection with Noisy Labels

arXiv:2610.05918v1 Announce Type: new Abstract: Existing data-driven infrared small target detection (ISTD) methods typically require large-scale datasets with accurate pixel-level annotations for mod

local-aiarxiv-cs-cv