Search: “models”

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

16 Jul 2026

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Tutorials

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

DGX agent

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

16 Jul 2026

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

researcharxiv-cs-lg

16 Jul 2026

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

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

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

RippleBench: Capturing Ripple Effects Using Existing Knowledge Repositories

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

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

10 Jul 2026

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

10 Jul 2026

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

10 Jul 2026

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

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

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

researcharxiv-cs-lg

8 Jul 2026

Tutorials

Canopy: A Heterograph Foundation Model for Metabolic Engineering

arXiv:2607.06224v1 Announce Type: new Abstract: Designing microbial strains that produce high-value chemicals at commercially viable titers remains a central challenge in metabolic engineering. Existi

tutorialsarxiv-cs-lg

8 Jul 2026

Fine-Tuning Integrity for Modern Neural Networks: Structured Drift Proofs via Norm, Rank, and Sparsity Certificates

model-releasesarxiv-cs-lg

arXiv:2604.04738v2 Announce Type: replace-cross Abstract: Fine-tuning is the dominant paradigm for adapting large machine learning models, yet current deployment pipelines provide no way to verify how

8 Jul 2026

Agentic-V2X: Small Language Model Agents for Deadline-Aware V2X Scheduling in 5G/6G Networks

arXiv:2607.04290v1 Announce Type: cross Abstract: Large Language Models (LLMs) are proposed as control interfaces for next-generation networks, but their latency, hallucinations, and lack of control g

local-aiarxiv-cs-ai

Alleviating Sparse Rewards by Modeling Step-Wise and Long-Term Sampling Effects in Flow-Based GRPO

arXiv:2602.06422v2 Announce Type: replace Abstract: Deploying GRPO on Flow Matching models has proven effective for text-to-image generation. However, existing paradigms typically propagate an outcome

Benchmarking API Drift in LLM-Generated Quantum Code Across Successive SDK Versions

arXiv:2607.04072v1 Announce Type: cross Abstract: Large language models can generate plausible quantum code, but it is unclear whether they can reliably target the specific software development kit (S

BVS: Bayesian Visual Search with Multimodal Large Language Model for Fine-grained Perception

arXiv:2607.03184v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) demonstrate impressive general capabilities, they struggle with fine-grained perception in ultra-high-res

Agents

CRISP: A Spatiotemporal Camera-Radar Backbone for Driving via Forecasting-Based World-Model Pretraining

arXiv:2607.04541v1 Announce Type: cross Abstract: Camera-radar (CR) fusion is a practical sensing configuration for autonomous driving, but existing models are typically trained with task-specific sup

agentsarxiv-cs-ai

Determinants and Limits of LLM Security-Tool Orchestration: A Study with HexStrike-AI

arXiv:2607.02873v1 Announce Type: cross Abstract: Large language model agents driving security tool suites over the Model Context Protocol are increasingly common. Yet the factors that bound their cap

DistillH-Mamba: A Hypergraph-Mamba-Based Knowledge Distillation Model for Efficient Impact Fall Detection

arXiv:2607.03156v1 Announce Type: new Abstract: Falls among the elderly represent a significant public health concern due to their prevalence, consequences, and societal burden. While deep learning ha

DuplexChat: Constructing Speaker-Separated Full-Duplex Dialogue Speech at Scale for Spoken Dialogue Language Modeling

arXiv:2607.04941v1 Announce Type: new Abstract: Full-duplex spoken dialogue models are trained on conversational speech in which each speaker is represented as a separate stream, but existing large-sc

researcharxiv-cs-cl

Forethought: Verifiable Reasoning from Neurosymbolic Primitive Programming

arXiv:2607.04096v1 Announce Type: new Abstract: Current agentic workflows usually involve decomposing user requests into sequences of tool calls with correctly resolved parameters, the results of whic

From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model

arXiv:2607.03279v1 Announce Type: new Abstract: Accurate regional weather prediction requires resolving fine-scale structure while remaining consistent with global dynamics. Traditional limited area m

local-aiarxiv-cs-lg

Applications

HiSAC: Hierarchical Sparse Activation Compression for Ultra-long Sequence Modeling in Recommenders

arXiv:2602.21009v2 Announce Type: replace-cross Abstract: Modern recommender systems leverage ultra-long user behavior sequences to capture dynamic preferences, but end-to-end modeling is infeasible i

applicationsarxiv-cs-cl

How Much of the Routing Gap Is Real? Decomposing the Router-to-Oracle Gap into Reproducible Specialist Advantage and Single-Draw Label Noise

model-releasesarxiv-cs-lg

arXiv:2607.03436v1 Announce Type: new Abstract: Routing among large language models (LLMs) promises better quality at lower cost, motivated by the reported gap between learned routers and a per-instan

Human-like Object Grouping in Self-supervised Vision Transformers

arXiv:2603.13994v2 Announce Type: replace-cross Abstract: Vision foundation models trained with self-supervised objectives achieve strong performance across diverse tasks and exhibit emergent object s

NRT-Bench: Benchmarking Multi-Turn Red-Teaming of LLM Operator Agents in Safety-Critical Control Rooms

arXiv:2606.20408v3 Announce Type: replace-cross Abstract: Large language model (LLM) agents are increasingly proposed as supervisory components for safety-critical systems, yet their robustness under

Applications

QuantFlow: A Federated Mamba-Based Post-Transformer Foundation Model for Time-Series Forecasting

arXiv:2607.02632v1 Announce Type: cross Abstract: Time-series forecasting supports decisions in finance, en-ergy, transportation, public health, and industrial monitoring. Recent foundation models imp

applicationsarxiv-cs-ai

RADIO1D: Elastic Representations for Condensed Vision Modeling

arXiv:2607.03624v1 Announce Type: cross Abstract: This paper challenges the assumption that vision-language models (VLMs) require fixed patch-based 2D vision features. Analyzing fine-tuned vision enco

safetyarxiv-cs-ai

Rating the Pitch, Not the Product: User Evaluations of LLMs Reflect Expectations More Than Performance

arXiv:2607.05113v1 Announce Type: new Abstract: Imagine two users interact with the same LLM. One has been told it is the cutting-edge flagship model; the other, an older, weaker model. They walk away

researcharxiv-cs-cl

TabQueryBench: A Query-Centric Benchmark for Synthetic Tabular Data

arXiv:2607.03926v1 Announce Type: cross Abstract: Synthetic tabular data support use cases like data sharing, model development under access restrictions, and rapid prototyping of analytical workflows

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test

arXiv:2505.08814v3 Announce Type: replace-cross Abstract: Deep neural networks (DNNs) play a crucial role in the field of artificial intelligence, and their security-related testing has been a promine

Training-Free Model Selection and Domain-Aware Score Calibration for First-Shot Anomalous Sound Detection

arXiv:2607.04526v1 Announce Type: cross Abstract: First-shot anomalous sound detection in DCASE Challenge Task 2 must flag anomalies of unseen machine types with a single threshold, without knowing wh

Tutorials

What Does a Discrete Diffusion Model Learn?

arXiv:2607.05381v1 Announce Type: cross Abstract: What does a discrete diffusion model learn: a denoiser, a score ratio, or a bridge plug-in predictor? At the level of jump rates, these are one object

tutorialsarxiv-cs-ai

CreativityPrism: A Cross-Domain Evaluation Framework for Large Language Model Creativity

arXiv:2510.20091v3 Announce Type: replace-cross Abstract: Creativity is often seen as a hallmark of human intelligence. While large language models(LLMs) are increasingly perceived as generating creat

local-aiarxiv-cs-ai

Many Voices, One Reward: Multi-Role Rubric Generation for LLM Judging and Reward Modeling

arXiv:2607.01830v1 Announce Type: new Abstract: Reliable reward and preference signals are critical for evaluating and optimizing large language models on open-ended tasks. Rubric-based judges offer a

researcharxiv-cs-lg

Multi-Rate Nonlinear Model Predictive Control for Wall-Supported Bipedal Locomotion of Quadrupedal Robots

arXiv:2607.01574v1 Announce Type: new Abstract: This paper presents a novel layered planning and control framework based on multi-rate nonlinear model predictive control (MR-NMPC) that enables quadrup

researcharxiv-cs-ro

PairCoder++: Pair Programming as a Universal Paradigm for Verified Code-Driven Multimodal and Structured-Artifact Generation

model-releasesarxiv-cs-cl

arXiv:2607.01883v1 Announce Type: new Abstract: Code is the medium through which large language models generate structured artifacts: charts, scientific figures, vector graphics, CAD models, 3D scenes

TUDUM: A Turkish-Thinking Reasoning Pipeline for Qwen3.5-27B

arXiv:2607.01927v1 Announce Type: cross Abstract: This paper presents TUDUM (Turkce Dusunen Uretken Model), a project pipeline for adapting a Qwen-family 27B thinking model toward Turkish reasoning. T

WorldSample: Closed-loop Real-robot RL with World Modelling

arXiv:2607.02431v1 Announce Type: cross Abstract: Reinforcement learning (RL) can overcome the demonstration-coverage limitation of imitation learning (IL) by allowing robots to improve through trial-

safetyarxiv-cs-ai

Crystalite: A Lightweight Transformer for Efficient Crystal Modeling

arXiv:2604.02270v2 Announce Type: replace-cross Abstract: Generative models for crystalline materials often rely on equivariant graph neural networks, which capture geometric structure well but are co

FrameONE: Hierarchical Motion Modeling for Universal Multi-View Echocardiographic Keyframe Detection

arXiv:2607.00748v1 Announce Type: new Abstract: Accurate detection of end-systole (ES) and end-diastole (ED) frames is fundamental to echocardiographic assessment. Existing methods are typically devel

safetyarxiv-cs-cv

Agents

Human-Machine Collaboration on Generative Meta-Learning: Model and Algorithm

arXiv:2607.00926v1 Announce Type: cross Abstract: Generalizing machine learning models to environments that differ from their training distribution remains a critical hurdle, particularly when data fr

agentsarxiv-cs-ai

Prompt2Effect: Training-Free Image-to-Video Model Specialization via LoRA Generation

arXiv:2606.13971v2 Announce Type: replace Abstract: While personalizing Image-to-Video (I2V) diffusion models with specific visual effects is increasingly demanded for high-end generation, current pra

safetyarxiv-cs-cv