Search: “models”

Where Animacy Lives in Large Language Models: Tracing the Circuits of the Animacy Concept

arXiv:2607.20995v1 Announce Type: new Abstract: Distinguishing animate from inanimate concepts in written language requires more than shallow text processing, as it involves recognizing complex select

researcharxiv-cs-cl

24 Jul 2026

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Local Ai

AdaHome: An Adaptive Smart Home Assistant using Local Small Language Models

DGX agent

arXiv:2607.18034v2 Announce Type: replace Abstract: Smart home assistants interpret a wide range of user commands, from explicit device control to underspecified and preference dependent requests. Whi

local-aiarxiv-cs-ai

23 Jul 2026

EvoThink: Evolving Thinking in Large Reasoning Models via Self-Pruning and Aha-Moment Preference Optimization

arXiv:2607.19962v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) often suffer from overthinking due to redundant verification steps. Existing approaches for mitigating overthinking, such

FedCC: A Low-Resource Federated Adaptation of Foundation Models for Robust Corpus Callosum localization in Fetal Ultrasound Images

model-releasesarxiv-cs-cv

arXiv:2607.18283v1 Announce Type: cross Abstract: Accurate localization of the corpus callosum (CC) in fetal ultrasound (US) images is crucial for the early identification of neurodevelopmental abnorm

Image Editing Models are Numerical Solvers

arXiv:2607.18787v1 Announce Type: new Abstract: We investigate whether a pretrained generative image-editing model can provide a common interface for numerical simulation. Physical inputs and solution

researcharxiv-cs-cv

LaCache: Exact Caching and Precision-Adaptive Inference for Diffusion Large Language Models

arXiv:2607.16339v2 Announce Type: replace Abstract: Diffusion-based Large Language Models(DLLMs) enable parallel generation via Semi-Autoregressive (SAR) decoding in text generation. However, current

Machine Can Automatically Discover Parametric Functions to Model HEP Data

arXiv:2607.19750v1 Announce Type: cross Abstract: In HEP data analyses, finding an adequate function to model binned data has largely relied on a manual process: guess a functional form by intuition,

NMR Elucidation as an Agentic Search Problem, Not a Modeling Problem

arXiv:2607.19406v1 Announce Type: new Abstract: Structural elucidation from Nuclear Magnetic Resonance (NMR) data remains a fundamental bottleneck across chemistry, materials science, and biology. We

agentsarxiv-cs-lg

On the Separability of Information in Diffusion Models

arXiv:2509.23937v5 Announce Type: replace-cross Abstract: Diffusion models transform noise into data by injecting information that was captured in their neural network during the training phase. In th

OSVE: One Step Video Editing with One Step Diffusion Models

arXiv:2607.19895v1 Announce Type: cross Abstract: Text-guided video editing with diffusion models is impractically slow, hindered by costly multi-step sampling and inversion. We present OSVE, the firs

PIER: Physics-Informed Environmental Retrieval for Time-Series Modeling

arXiv:2607.20230v1 Announce Type: new Abstract: Accurate modeling of environmental systems is fundamental to scientific understanding and decision-making, yet remains challenging because observations

PRISM-DR: Per-lesion Retinal Inference with Specialist Models for Diabetic Retinopathy

arXiv:2607.19864v1 Announce Type: cross Abstract: Diabetic retinopathy is a leading cause of preventable blindness; its early lesions are small, low contrast, and easily missed in manual screening. Mo

Hardware

ReRAM-aware Model Finetuning addressing I-V Non-linearity and Retention Errors

arXiv:2606.17471v3 Announce Type: replace Abstract: Traditional CPU, GPU, and NPU architectures are increasingly limited by the von Neumann bottleneck. While In-Memory Computing (IMC) using ReRAM cros

hardwarearxiv-cs-lg

Test-Time Training for Modality Order Consistency in Vision-Language Models

arXiv:2607.20351v1 Announce Type: cross Abstract: We find that vision-language models are sensitive to a specific semantically irrelevant change: the order in which the image and question are presente

researcharxiv-cs-cl

The Two-Process Theory of Machine Self-Report

arXiv:2607.20082v1 Announce Type: new Abstract: Language models are increasingly asked to self-report, informing safety evaluations, public understanding, and model-welfare debates. Yet their reports

safetyarxiv-cs-cl

TINY_SCHILLER: A Drop-In German Drama Corpus for Small Language Models

arXiv:2607.19992v1 Announce Type: cross Abstract: tiny_schiller closes the small-language-model prototyping, fine-tuning, education, and research gap for German literary text, providing a single-file,

applicationsarxiv-cs-ai

Cyclone: Diffusion Model for Cycle-Consistent Weather Editing from Unpaired Driving Data

arXiv:2607.13927v1 Announce Type: new Abstract: Reliable perception under diverse weather conditions remains a major challenge for autonomous driving systems. A common strategy to improve robustness i

agentsarxiv-cs-cv

Disentangling Knowledge States with Ability and Proficiency Modeling for Knowledge Tracing

arXiv:2607.13103v1 Announce Type: cross Abstract: Knowledge tracing (KT) aims to predict students' future performance by modeling their evolving knowledge states from historical interactions. Existing

safetyarxiv-cs-ai

GFlowRL: Scaling Distribution-Matching RL to Large Language Models

arXiv:2607.13394v1 Announce Type: cross Abstract: Generative Flow Networks (GFlowNets) offer a promising alternative to reward-maximizing reinforcement learning (RL) for large reasoning models, encour

IMMNet: Hybrid Fusion of Model-based and Data-driven Approaches for Maneuvering Target Tracking

arXiv:2607.13573v1 Announce Type: cross Abstract: Maneuvering target tracking in three-dimensional space remains a challenging problem due to complex motion dynamics and model mismatch. To address thi

tutorialsarxiv-cs-ai

PokeNet: Learning Kinematic Models of Articulated Objects from Human Observations

arXiv:2602.02741v2 Announce Type: replace Abstract: Articulation modeling enables robots to learn joint parameters of articulated objects for effective manipulation which can then be used downstream f

tutorialsarxiv-cs-ro

The Hyperspherical Geometry of CLIP Latent Space: A Semantic Mixture Model

arXiv:2607.13660v1 Announce Type: new Abstract: Contrastive Language-Image Pretraining (CLIP) representations form a semantic embedding space governed by cosine similarity, reflecting an intrinsic hyp

tutorialsarxiv-cs-lg

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry

arXiv:2607.13046v1 Announce Type: new Abstract: We develop a framework for the information discarded by machine learning models whose inputs carry a Lie group action. Given a representation pi of a Li

BattVAE-GP: Generative Modeling of Long-Horizon Battery Degradation with Uncertainty Quantification

arXiv:2607.11943v1 Announce Type: cross Abstract: Long-horizon physics-based simulations of battery degradation provide mechanistic insight but remain computationally expensive, limiting their use for

Compos3D: Interactive Part-Based Composition for Creative Control in Generative 3D Models

arXiv:2607.12193v1 Announce Type: cross Abstract: While generative AI has unlocked new opportunities for 3D content creation, current workflows often rely on multiple regenerations, which provides lim

safetyarxiv-cs-cv

DermDepth: Toward Monocular Metric Scale 3D Reconstruction Models for Dermatology

arXiv:2607.13010v1 Announce Type: new Abstract: Dermatological practice routinely involves measuring and tracking lesion size, morphology and texture, as critical components of wound or skin cancer sc

applicationsarxiv-cs-cv

Generating Developable 3D Molecules via Pocket-Conditioned Diffusion and Property-Aware Optimization

model-releasesarxiv-cs-lg

arXiv:2607.12349v1 Announce Type: new Abstract: Drug discovery and development is time-consuming and resource-intensive, motivating computational approaches such as diffusion models for de novo drug d

Less Experts, Faster Decoding: Cost-Aware Speculative Decoding for Mixture-of-Experts

model-releasesarxiv-cs-ai

arXiv:2607.12696v1 Announce Type: cross Abstract: Sparse Mixture-of-Experts (MoE) models have become an important approach for scaling Large Language Models (LLMs), but their inference efficiency depe

RepTran: Search-Based Repair of Transformer Models

arXiv:2607.11193v2 Announce Type: replace-cross Abstract: To ensure the overall quality of AI-enabled software, not only traditional software components but also AI components need to be tested and re

RippleBench: Capturing Ripple Effects Using Existing Knowledge Repositories

model-releasesarxiv-cs-ai

arXiv:2512.04144v3 Announce Type: replace Abstract: Targeted interventions on language models, such as unlearning or model editing, aim to modify specific information, but their effects often propagat

VISA: VLM-Guided Instance Semantic Auditing for 3D Occupancy World Models

arXiv:2606.13460v2 Announce Type: replace Abstract: Semantic 3D occupancy provides a voxelized world state for autonomous driving and robot decision making, but object and rare-class errors can affect

agentsarxiv-cs-cv

Local Ai

BiSCo-LLM: Lookup-Free Binary Spherical Coding for Extreme Low-Bit Large Language Model Compression

arXiv:2607.08643v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly constrained by memory capacity, weight bandwidth, and checkpoint storage during deployment. Existing low-b

local-aiarxiv-cs-lg

Drift-Aware Temporal Graph Rewiring (DATGR) for Adaptive Semantic Modeling in Biomedical Text

arXiv:2607.08490v1 Announce Type: new Abstract: Biomedical language evolves rapidly as new discoveries emerge, causing traditional text models to lose semantic fidelity over time. Static embeddings an

Local Ai

Learning mathsf{AC}^0 under Locally Sampleable Graphical Models

arXiv:2607.08303v1 Announce Type: new Abstract: The problem of learning constant-depth circuits holds profound implications for computational learning theory. In a seminal result, by introducing the l

local-aiarxiv-cs-lg

LongE2V: Long-Horizon Event-based Video Reconstruction, Prediction, and Frame Interpolation with Video Diffusion Models

arXiv:2607.08770v1 Announce Type: new Abstract: Recovering high-quality video from sparse event streams is a challenging task. Regression methods often blur textures, while existing generative models

safetyarxiv-cs-cv

Texture Representations in Deep Vision Models: Comparing CNNs, Vision Transformers, and Human Perception

arXiv:2607.08321v1 Announce Type: new Abstract: In computational vision science, Convolutional Neural Networks (CNNs) have emerged as a popular model of biological vision because of the alignment they

safetyarxiv-cs-cv

Understanding and Mitigating the Video-Action Generalization Gap via Temporal Ratio

model-releasesarxiv-cs-cv

arXiv:2607.08127v1 Announce Type: new Abstract: Generative video foundation models exhibit strong compositional priors, yet world-action models (WAMs) and video-action models (VAMs) often lose these p

Unveiling Public Opinion: A Study of Sentiment Analysis Using LSTM and Traditional Models

arXiv:2607.07772v1 Announce Type: new Abstract: In this age of social media, sites like Twitter have become meeting places for people to share their views and feelings on a wide range of issues and cu

researcharxiv-cs-cl

Write-Protected Discrete Bottlenecks for Language-Grounded World Models: A Structural Limitation and Sufficient Fix

arXiv:2607.08312v1 Announce Type: new Abstract: How should language interface with a world model's discrete symbol system? The dominant paradigm -- end-to-end injection of LLM/VLM features into robot

tutorialsarxiv-cs-lg

Hardware

DYNA-PRUNER: Input-Adaptive Data-Model Co-Pruning for Efficient and Scalable Spatio-Temporal Media Prediction

arXiv:2606.15346v2 Announce Type: replace Abstract: Spatio-temporal prediction supports radar/satellite nowcasting and city-scale traffic monitoring, but modern models are often too expensive for real

hardwarearxiv-cs-cv

ECHO: Ego-Centric modeling of Human-Object interactions

arXiv:2508.21556v3 Announce Type: replace Abstract: Modeling human-object interactions (HOI) from an egocentric perspective is a critical yet challenging task, particularly when relying on sparse sign

researcharxiv-cs-cv

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI

arXiv:2607.06982v1 Announce Type: new Abstract: Convolutional neural networks (CNNs) have demonstrated encouraging results in image classification tasks. However, the prohibitive computational cost of

researcharxiv-cs-cv

Future Confidence Distillation in Large Language Models

arXiv:2607.07626v1 Announce Type: cross Abstract: Reliable confidence estimation is essential for deploying large language models (LLMs) in confidence-aware systems, where downstream decisions such as

agentsarxiv-cs-ai

Local Ai

Memory Scarcity, Open Models, and the Restructuring of the AI Industry, 2026-2030 -- A quantitative scenario analysis of inference economics, training-cost divergence, and infrastructure solvency

arXiv:2607.07207v1 Announce Type: cross Abstract: We analyze how four forces restructure the AI industry over 2026-2030: the DRAM/HBM price surge, frontier-capable open-weight models (GLM-5.2), rapid

local-aiarxiv-cs-ai

Tensorized algorithms and scalable filtering methods for hidden Markov and factorial hidden Markov models

arXiv:2607.07008v1 Announce Type: cross Abstract: A common method for the representation and analysis of time-series data is the hidden Markov model (HMM), where each observation is associated with a

applicationsarxiv-cs-lg

Validate the Dream Before You Trust Its Verdict: Admissibility for World-Model Simulators

arXiv:2607.07196v1 Announce Type: cross Abstract: Across robotics, World Models (WMs) are increasingly used to evaluate action policies by simulating the consequences of actions in an imagined world,

safetyarxiv-cs-ai

A Gibbs posterior sampler for inverse problem based on prior diffusion model

arXiv:2602.11059v2 Announce Type: replace-cross Abstract: This paper addresses the issue of inversion in cases where (1) the observation system is modeled by a linear transformation and additive error

8 Jul 2026

Abductive Corroboration of Probabilistic AI Models for Forensic Synthetic Media Detection