Search: “latent-space”

Examining Social Attribution in LLM Reasoning: A Theory-Guided Probing Methodology

model-releasesarxiv-cs-ai

arXiv:2610.12022v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in sociotechnical systems where social attribution, the reasoning process attributing external

9 Oct 2026

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Model Releases

Fluid-Gen-Zero: Grounding Pretrained Video Generators in Physics without Training

DGX agent

arXiv:2610.10984v1 Announce Type: new Abstract: We present Fluid-Gen-Zero, a training-free framework for physics-aware fluid-object interaction video generation that decouples physical reasoning from

model-releasesarxiv-cs-cv

9 Oct 2026

LR-V2X: Loss-Resilient Collaborative Perception under Low-Bandwidth Communication

model-releasesarxiv-cs-cv

arXiv:2610.11264v1 Announce Type: new Abstract: Given the inherent unpredictability of packet loss in vehicular wireless communications, V2X collaborative perception can yield practical benefits only

9 Oct 2026

Breaking Adversarial Transferability in Fine-Tuned Speech Recognition

arXiv:2610.09109v1 Announce Type: new Abstract: Many organizations fine-tune publicly available pretrained Automatic Speech Recognition (ASR) models and deploy them in black-box settings, assuming lim

safetyarxiv-cs-lg

8 Oct 2026

Quantifying Volumetric Risk: Class-Aware Asymmetric Weighted Conformal Prediction for 3D Medical Image Segmentation

model-releasesarxiv-cs-cv

arXiv:2610.09392v1 Announce Type: new Abstract: Reliable volumetric segmentation is critical for clinical diagnostics, yet foundation models such as MedSAM remain deterministic and lack calibrated unc

8 Oct 2026

Scalable Patch-Level Self-Supervised Learning

arXiv:2610.10013v1 Announce Type: new Abstract: Self-supervised learning (SSL) at scale produces powerful visual representations. However, most scalable SSL methods rely on ad hoc combinations of mult

8 Oct 2026

Atom-JEPA: Joint-Embedding Predictive Architecture for 3D Atomistic Systems

arXiv:2610.08400v1 Announce Type: cross Abstract: Large-scale self-supervised pretraining has reshaped modern machine learning, substantially advancing the ability of language and vision models to gen

researcharxiv-cs-ai

Latent space bias directions in LLMs capture confidence, not fairness

arXiv:2610.08559v1 Announce Type: cross Abstract: Activation steering has gained popularity as a lightweight inference-time debiasing technique for large language models. However, prior work reports t

Tutorials

Learning Disentangled Representations with Quantum Variational Autoencoders

arXiv:2610.07196v1 Announce Type: cross Abstract: Variational autoencoders are powerful representation learning models that map complex data into low-dimensional latent spaces, enabling the discovery

tutorialsarxiv-cs-lg

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

model-releasesarxiv-cs-ai

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

EagleDepth: Efficient Fine-Grained Depth Estimation via Pixel Diffusion Decoder

arXiv:2610.04554v1 Announce Type: new Abstract: Recovering detailed geometry from high-resolution images is critical for precise perception of the surroundings and objects. However, existing methods w

Local Ai

MercerFlow: Flow Matching in a Kernel-Induced Latent Space for Probabilistic Forecasting

arXiv:2610.06039v1 Announce Type: new Abstract: Recent work has shown that probabilistic flow matching for time series forecasting benefits from a data-matched prior. The resulting prior introduces lo

local-aiarxiv-cs-lg

MGPO: Manifold-Guided Diffusion Alignment for Task-Aware Dataset Distillation

arXiv:2610.05252v1 Announce Type: new Abstract: Diffusion-based dataset distillation (DD) suffers from a fundamental objective mismatch: likelihood-driven diffusion models prioritize density approxima

Local Ai

No Concept Escapes the Audit: Auditing-Aware Unlearning for Verifiable Concept Erasure in Diffusion Models

arXiv:2610.05401v1 Announce Type: new Abstract: Text-to-image diffusion models can generate prohibited content, which motivates concept erasure through machine unlearning. Most erasure methods interve

local-aiarxiv-cs-lg

A Two-Stage Cascade for Near-Real-Time Forest Anomaly Detection from Sentinel-1 SAR Time Series

arXiv:2610.02763v1 Announce Type: new Abstract: Tropical forest monitoring is essential for global climate stability and biodiversity preservation. To address the urgent need for rapid, reliable detec

Adaptive Second-Order Solvers for Fast Stochastic Diffusion Sampling

arXiv:2610.03034v1 Announce Type: cross Abstract: Diffusion models rely on numerical solvers requiring time-discretization, which has a large influence on the tradeoff between sampling cost and qualit

researcharxiv-cs-cl

Causal discovery identifies pathways linking physical activity to dementia risk in the UK BioBank

arXiv:2610.02221v1 Announce Type: cross Abstract: Physical Activity (PA) is consistently associated with lower risk of dementia, yet the mechanism linking PA to dementia prevention remain incomopletel

researcharxiv-cs-ai

DISSOLVR: An Interpretable and Fast Framework for Aqueous and Organic Solubility Prediction

model-releasesarxiv-cs-lg

arXiv:2610.02574v1 Announce Type: new Abstract: High-fidelity solubility prediction is fundamental to pharmaceutical development and environmental partitioning, where accurate modeling must couple mol

Less Decoder is More Encoder: Geometric Representation Learning from Novel View Synthesis

arXiv:2610.03717v1 Announce Type: cross Abstract: This paper examines the role of Novel View Synthesis (NVS) in geometric representation learning. In principle, NVS should reason about 3D scene struct

researcharxiv-cs-ai

Applications

Predictor-Guided Latent Space Codon Optimization for Maximizing Protein Expression

arXiv:2610.03098v1 Announce Type: new Abstract: Codon optimization, the process of selecting synonymous codons to improve mRNA translation efficiency and protein expression, is central to therapeutic

applicationsarxiv-cs-ai

SlimKV: Joint Token-Feature KV Cache Compression with Reconstruction-Free Beacon Attention

arXiv:2610.02953v1 Announce Type: new Abstract: Long-context LLM serving is increasingly bottlenecked by KV-cache memory, especially in resource-constrained scenarios. Among existing KV-cache compress

Getting Out and Getting Back: World and Behavior Grounding in Real2Sim2Real Co-Training

arXiv:2610.00821v1 Announce Type: new Abstract: Simulation can expand scarce real demonstrations for co-training, yet how world fidelity and similarity to human behavior affect policy performance rema

safetyarxiv-cs-ro

2 Oct 2026

Cycle-Aware Autoencoder with Cross-SignalConsistency for Railway Door Anomaly Detection

arXiv:2609.39035v1 Announce Type: cross Abstract: Passenger access doors are safety-critical subsystems in railway vehicles, yet detecting abnormal door behavior in real operation is challenging becau

1 Oct 2026

Applications

Ghost in the Encoder: Decodable Artist Identity Representations in Lyrics-to-Song Generation

arXiv:2609.39552v1 Announce Type: cross Abstract: Text-to-song generation models can be prompted to imitate specific artists or regurgitate entire songs from their training data. Although these phenom

applicationsarxiv-cs-lg

1 Oct 2026

Safety of Latent Communication in Multi-Agent Systems

arXiv:2609.39788v1 Announce Type: new Abstract: Latent communication enables multi-agent systems to exchange information directly in internal representation space, reducing the token, computation, and

1 Oct 2026

AutoMark: Enabling Autoresearch to Discover Better LLM Watermarks

model-releasesarxiv-cs-lg

arXiv:2609.37310v1 Announce Type: cross Abstract: With LLM watermarking being deployed commercially and now required by regulations, improving its reliability and effectiveness has become crucial. Yet

Agents

Cooperative Multi-Agent Vision-Language-Action Models via Reinforced Fine Tuning

arXiv:2609.36588v1 Announce Type: cross Abstract: We study reinforcement learning (RL) methods for cooperative multi-agent Vision-Language-Action (VLA) models. This problem is challenging because VLAs

agentsarxiv-cs-ai

CoRe: Co-Evolving Reward Models for Mitigating Latent Reward Hacking in Video Diffusion Models

arXiv:2609.36245v1 Announce Type: new Abstract: Latent reward models (LRMs) enable efficient alignment of video diffusion models by scoring intermediate states directly in latent space. However, we fi

Disentangling Spurious Correlations in Vision-Language-Action Models via Predicting Domain-Invariant Latent Lookahead

arXiv:2609.37165v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models remain brittle under visual distribution shifts, often relying on spurious correlations tied to domain-specific fact

safetyarxiv-cs-ro

Agents

DSWM: Decomposed Spatio-Temporal World Model for Demand-Driven UAV Base Station Repositioning

arXiv:2609.36845v1 Announce Type: cross Abstract: Uncrewed aerial vehicle base stations (UAV-BSs) are expected to cover traffic demand that shifts across space and time, yet most repositioning schemes

agentsarxiv-cs-ai

Hardware

Embedded Bi-Temporal Building Damage Assessment for On-Board Data Reduction

arXiv:2609.37013v1 Announce Type: cross Abstract: Rapid assessment of building damage after natural disasters is essential to support emergency response. Earth Observation satellites can acquire relev

hardwarearxiv-cs-ai

AeroJEPA: Learning Semantic Latent Representations for Scalable 3D Aerodynamic Field Modeling

arXiv:2605.05586v2 Announce Type: replace Abstract: High-fidelity CFD is essential for aerodynamic design, but repeated simulations are computationally expensive, motivating surrogate models for rapid

ANaLOG: Anisotropic Native-Latent Operator Guidance for Solving Inverse Problems

arXiv:2609.31933v1 Announce Type: cross Abstract: Native-latent guidance is a recent paradigm for solving inverse problems with latent diffusion models. It replaces repeated evaluations of the image-s

Knowledge-Driven XRD Phase Identification via Multi-View Retrieval and Explanation

arXiv:2609.31888v1 Announce Type: cross Abstract: X-ray diffraction (XRD) is a experimental technique for determining the phase composition and structure of crystalline materials. However, interpretin

Principal Steering Subspaces for Online Adaptation of Frozen Generative Robot Policies

model-releasesarxiv-cs-ro

arXiv:2609.33765v1 Announce Type: new Abstract: Generative robot policies provide expressive behavior priors, but updating a large diffusion or flow-matching model through online interaction is costly

RepFlow: Reciprocal Supervision Improves Generation and Representation in Flow Models

arXiv:2609.33217v1 Announce Type: new Abstract: Generative models learn visual structure through denoising, yet their internal states are entangled with both noise level and network depth, making it d

Resolving State-Representation Mismatch: State-Space Visual Reasoning for Open-Loop VLA Planning

arXiv:2609.33412v1 Announce Type: new Abstract: Despite rapid progress in vision-language-action (VLA) models, existing reasoning paradigms still face a fundamental state-representation mismatch in op

Self-Reconstruction Dynamics for Autoencoder Reconstruction Refinement

arXiv:2609.32268v1 Announce Type: new Abstract: Standard autoencoder (AE) inference uses a single encoder-decoder pass, though the latent may not be optimal for each sample under a fixed decoder. We a

When World Models Lie: Adaptive Safety Analysis Under Wrong Imaginations

arXiv:2609.34300v1 Announce Type: new Abstract: World models offer a powerful substrate for safety reasoning in high-dimensional robotic systems, but they are also fallible: their predictions can be b

safetyarxiv-cs-ro

Beyond Empirical Support: Structured Outlier Generation via Sinkhorn Optimal Transport

arXiv:2609.31470v1 Announce Type: cross Abstract: Outliers are essential for evaluating and improving the robustness of machine learning systems, especially when future distributions may differ signif

28 Sept 2026

GyroNovo: Error-Guided Fragment Imputation with Mass-Aware Attention for extit{De Novo} Peptide Sequencing

arXiv:2609.30542v1 Announce Type: new Abstract: De novo peptide sequencing from tandem mass spectra is essential for identifying peptides without relying on reference databases. Despite advances in de

safetyarxiv-cs-lg

28 Sept 2026

Long-Tail Adaptive Flow Matching with Explicit Conditional Consistency Guidance for Precise Multimodal Face Synthesis

arXiv:2609.29581v1 Announce Type: new Abstract: Although diffusion-based methods have substantially improved the controllability of multimodal face synthesis, their semantic alignment remains suboptim

25 Sept 2026

AI-Driven Neural Surrogates for In Silico Design of Cognitive-Affective Neuromodulation Targets

arXiv:2609.27729v1 Announce Type: cross Abstract: In neuropsychiatry, the primary goal is often not only to decode brain activity but to change it, for example to lessen a negative affective bias or a

24 Sept 2026

Starter-Iterator Neural Operator: A Unified Architecture for High-Fidelity Forward and Inverse PDE Problems

model-releasesarxiv-cs-lg

arXiv:2606.18305v2 Announce Type: replace-cross Abstract: Operator learning is an emerging field at the intersection of machine learning and scientific computing. By learning mappings between function

24 Sept 2026

Local Ai

Discovery-Driven Integration of Disjoint Tables via Text

arXiv:2609.26658v1 Announce Type: cross Abstract: Integrating heterogeneous datasets within data lakes is a critical challenge, particularly for semantically related tables that lack the explicit attr

local-aiarxiv-cs-cl

23 Sept 2026

Dissecting Hierarchical Reasoning Models: A Mechanistic Study

arXiv:2609.22197v1 Announce Type: new Abstract: We study Hierarchical Reasoning Model (HRM), a representative hierarchical Transformer-based latent reasoning model with many variants, on Sudoku, Maze,

22 Sept 2026

From Latent Biomarkers to Clinical Rules: Embedding-Guided Rule Mining and Attribution-Based Translation for Interpretable Tabular Learning

arXiv:2609.22155v1 Announce Type: new Abstract: Clinical decision support tools are most useful when accurate predictions are accompanied by understandable explanations. Rule-based models provide tran

22 Sept 2026

PhysReflect: Geometry and Perception Guided Diffusion for Physically-Plausible Mirror Reflections

arXiv:2609.23442v1 Announce Type: new Abstract: Diffusion models generate high-quality images, yet often violate the physical laws governing mirror reflections. Reflections often suffer from geometric