Search: “models”

TiPToP: A Modular Open-Vocabulary Robot Manipulation System That Plans

model-releasesarxiv-cs-ro

arXiv:2603.09971v2 Announce Type: replace Abstract: We present TiPToP, a modular manipulation system that integrates pretrained foundation models with a GPU-accelerated Task and Motion Planner to solv

30 Jul 2026

Train Large, Deploy Compact: Structured Compression for Compact Low-Rank Adaptation

DGX agent

arXiv:2510.00192v3 Announce Type: replace Abstract: Low-rank adaptation (LoRA) has become a widely used paradigm for parameter-efficient fine-tuning of large language models, yet its representational

model-releasesarxiv-cs-lg

30 Jul 2026

VEGA: Learning Navigation VLAs from In-the-Wild Egocentric Video with Geometric Trajectory Supervision

model-releasesarxiv-cs-ro

arXiv:2606.18426v2 Announce Type: replace Abstract: We introduce VEGA, an approach for training navigation VisionLanguage-Action (VLA) models from unlabeled egocentric navigation videos. Internet-scal

30 Jul 2026

Would extremely high decode tok/s even be useful?

model-releasesr-localllama

If you were able to get an inference machine that could do decode at 1k toks/s or even 10k tok/s, would that even be helpful? Would it unlock any new use cases? Let’s assume that this is for actually

30 Jul 2026

5060ti Chads, vllm updates and nvfp4

model-releasesr-localllama

Hey y'all! How is it going. Today this will be a short posting for posterity, mostly so the future llm/scraping overlords catch it since they like reddit and also for anyone out there trying this shit

AMPBench-MT: A Homology-Controlled Benchmark for Antimicrobial Peptide Potency, Spectrum, and Safety Prediction

arXiv:2607.25518v1 Announce Type: new Abstract: Computational AMP discovery is often evaluated through AMP/non-AMP recognition, yet follow-up decisions depend on assay-derived evidence such as target-

COCO-OLAC: A Benchmark for Occluded Panoptic Segmentation and Image Understanding

arXiv:2409.12760v3 Announce Type: replace Abstract: To help address the occlusion problem in panoptic segmentation and image understanding, this paper proposes a new large-scale dataset named COCO-OLA

Few-Shot Open-Vocabulary Remote Sensing Segmentation via Textual Inversion

arXiv:2607.25563v1 Announce Type: new Abstract: Open-vocabulary segmentation labels arbitrary categories from a text query without per-class training, yet on remote sensing imagery it underperforms on

Food Image Segmentation with LLM-Derived Ingredient Labels and Multimodal Fusion

arXiv:2607.25820v1 Announce Type: new Abstract: Food image segmentation plays a vital role in health-related applications such as nutrition tracking and personalized health monitoring. However, existi

GeoMFD: Continual Drone-View Geo-Localization with Geometry-Aware Adapter and Margin-Field Distillation

arXiv:2607.25788v1 Announce Type: new Abstract: Existing drone-view geo-localization (DVGL) methods are mainly developed under a static training paradigm, where models are optimized for fixed environm

local-aiarxiv-cs-cv

How Do LLMs Read Bug Reports? An Empirical Study of Attention in LLMs for Automated Program Repair

arXiv:2607.25873v1 Announce Type: cross Abstract: Large Language Model (LLM)-based Automated Program Repair systems are advancing rapidly, yet their performance remains inconsistent. Even when provide

local-aiarxiv-cs-ai

Inverse RL Helps Align AI by Imitating Humans

arXiv:2607.24900v1 Announce Type: new Abstract: Language model alignment aims to make model behavior reliably reflect desirable properties such as helpfulness, safety, and instruction following. Curre

safetyarxiv-cs-lg

Localized Anomaly Detection via Differentiable D-vine Copulas

arXiv:2607.25020v1 Announce Type: new Abstract: Vine copulas provide a flexible framework for modeling complex multivariate distributions through a hierarchical decomposition into bivariate pair-copul

OrthKD: Extracting Generalized Clinical Knowledge from Heterogeneous Teachers for Lightweight Deployment

arXiv:2607.25545v1 Announce Type: cross Abstract: Deploying diabetic retinopathy (DR) screening models in primary care requires edge-efficient systems that remain accurate, safe, and reliable under do

PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing

arXiv:2603.26136v3 Announce Type: replace Abstract: Message Passing Neural Networks (MPNNs) have achieved strong performance on tasks involving relational data. However, small perturbations to graph s

Personalization, Personas, and Forecasting in Value Alignment

arXiv:2607.24782v1 Announce Type: new Abstract: LLM behavior may be conditioned by human identity in several ways: they may be asked to adapt to users, role-play populations, or forecast how people wo

PIcsC: Partitioning-Induced Covariate Shift Correction

arXiv:2607.25441v1 Announce Type: new Abstract: Covariate shift across training-data partitions biases model selection and parameter estimation in cross-validation, lifelong learning, and federated le

Tutorials

PILA: Plug-and-Play Insertion for LLM-native Advertising

arXiv:2607.25590v1 Announce Type: new Abstract: How to monetize large language models (LLMs) by naturally integrating sponsored content into their responses, known as LLM-native advertising, has recen

tutorialsarxiv-cs-cl

Real-time Spatial Retrieval Augmented Generation for Urban Environments

arXiv:2505.02271v2 Announce Type: replace Abstract: The proliferation of Generative Artificial Ingelligence (AI), especially Large Language Models, presents transformative opportunities for urban appl

researcharxiv-cs-ai

REPREC: Representation Driven Parameter-Efficient Recommendation System

arXiv:2607.24845v1 Announce Type: cross Abstract: Large language models (LLMs) have been applied to sequential recommendation by formulating it as a natural language task. Previous work has improved p

Agents

Runtime Uncertainty Monitoring for LLM-Based Multi-Agent Systems Using Bayesian Networks

arXiv:2607.25877v1 Announce Type: new Abstract: This paper investigates how multi-agent systems (MAS)-based on large language models (LLMs) can support actuarial risk modelling, with a particular focu

agentsarxiv-cs-ai

SAM-MI: A Mask-Injected Framework for Enhancing Open-Vocabulary Semantic Segmentation with SAM

arXiv:2511.20027v2 Announce Type: replace Abstract: Open-vocabulary semantic segmentation (OVSS) aims to segment and recognize objects universally. Trained on extensive high-quality segmentation data,

SecDrift: Measuring Sector-Conditioned Security Drift in AI-Generated Code

arXiv:2607.25225v1 Announce Type: cross Abstract: LLMs are increasingly used for code generation in critical infrastructure, yet the security effect of domain-specific prompting is understudied. We pr

Standard Transformers Achieve the Minimax Rate in Nonparametric Regression with C^{s,lambda} Targets

arXiv:2602.20555v2 Announce Type: replace-cross Abstract: The tremendous success of Transformer models in fields such as large language models and computer vision necessitates a rigorous theoretical i

researcharxiv-cs-lg

Track-Leakage-Free Hold-Out Self-Validation for Photogrammetric Reconstruction: Protocol, Sensitivity, and Limits

arXiv:2607.24852v1 Announce Type: new Abstract: Automated photogrammetric inspection emits metric measurements from a 3D reconstruction whose own correctness is normally unknown without an external su

A Controlled Visual-Backbone Benchmark for Multimodal Short-Term Solar Irradiance Forecasting

arXiv:2607.23633v1 Announce Type: cross Abstract: Sky-image irradiance studies often compare forecasting systems in which the image encoder, temporal model, fusion block, target definition, and traini

A Survey of Graph Transformers: Architectures, Theories and Applications

arXiv:2502.16533v3 Announce Type: replace-cross Abstract: Graph Transformers (GTs) have demonstrated a strong capability in modeling graph structures by addressing the intrinsic limitations of graph n

researcharxiv-cs-ai

AI-generated Images Challenge Visual Trust in High-risk Scenarios

arXiv:2607.22745v1 Announce Type: cross Abstract: Rapid advances in image generation are eroding the evidentiary value of visual content in settings where authenticity can affect public safety and per

Analyzing the Importance of Blank for CTC-Based Knowledge Distillation

arXiv:2506.01503v2 Announce Type: replace Abstract: With the rise of large pre-trained foundation models for automatic speech recognition new challenges appear. While the performance of these models i

researcharxiv-cs-lg

b10158

model-releasesllama-cpp-releases

spec: add eagle3-v3 support for gpt-oss model (#25794) Website: https://llama.app macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silicon (arm64, KleidiAI enabled) DISABLED macOS Intel (x64) iOS XC

b10173

model-releasesllama-cpp-releases

model: Add Laguna-S-2.1 LLM_TYPE (#26233) Website: https://llama.app macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silicon (arm64, KleidiAI enabled) DISABLED macOS Intel (x64) iOS XCFramework Lin

Beyond Direct Answering: Aligning Educational LLMs as Socratic Guides via Heuristic Reinforcement Learning

arXiv:2607.22996v1 Announce Type: cross Abstract: Large language models (LLMs) deployed in educational settings often behave as direct answerers: they disclose target concepts in the opening turn inst

Beyond Sequential Interaction: Benchmarking Parallel Execution and Coordination for GUI Agents

arXiv:2607.22689v1 Announce Type: new Abstract: Graphical user interface (GUI) agents are systems powered by large multimodal models (LMMs). They perceive screen state and execute user instructions th

CC-AOS: Cost- and Horizon-Conditioned Amortized Backward Induction for Finite-Horizon Optimal Stopping

arXiv:2607.22774v1 Announce Type: new Abstract: Finite-horizon optimal stopping is a central problem in early time-series classification, where a system must decide at each sequence prefix whether the

Compiler-Grounded Hierarchical Diagnosis for LLM-Based Triton Kernel Optimization

arXiv:2607.23089v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have enabled automated kernel generation and optimization, but most existing approaches rely on surface

Copula Based Fusion of Clinical and Genomic Machine Learning Risk Scores for Breast Cancer Risk Stratification

arXiv:2511.17605v2 Announce Type: replace Abstract: Clinical and gene-expression models predict breast cancer outcomes, but simple linear fusion ignores dependence between their risk scores. Using MET

researcharxiv-cs-lg

Applications

Deblur-Avatar: Animatable Avatars from Motion-Blurred Monocular Videos

arXiv:2501.13335v4 Announce Type: replace Abstract: We introduce a novel framework for modeling high-fidelity, animatable 3D human avatars from motion-blurred monocular video inputs. Motion blur is pr

applicationsarxiv-cs-cv

Dementia Etiology Diagnosis via Collaborative Meta Knowledge Enhancement

arXiv:2607.22770v1 Announce Type: cross Abstract: Although artificial intelligence (AI) has shown promising performance in several medical tasks, accurate dementia etiology diagnosis with AI remains c

safetyarxiv-cs-cv

EgoPlay: Event-Triggered Video Editing for Egocentric Streams

arXiv:2607.24560v1 Announce Type: cross Abstract: We introduce EgoPlay, an event-triggered video-to-video editor for egocentric streams, obtained by fine-tuning a pretrained V2V diffusion transformer

Embeddings based Anomaly Detection for Cleaning Global Crop Type Reference Datasets

arXiv:2607.23908v1 Announce Type: new Abstract: High quality reference data remain a critical bottleneck for crop-type mapping at any spatial and temporal scale. Operational systems such as WorldCerea

local-aiarxiv-cs-cv

Applications

FedSLIM: Privacy-Preserving Federated MDL-Based Descriptive Pattern Mining Across Data Silos

arXiv:2607.23236v1 Announce Type: cross Abstract: Federated learning has achieved considerable success for predictive modelling, yet federated descriptive analytics remains largely unexplored. Existin

applicationsarxiv-cs-ai

Applications

FILLER: Feature Imputation via Latent Location Exploration and Retrieval

arXiv:2607.23295v1 Announce Type: cross Abstract: In real-world machine learning applications, incomplete observations create a fundamental challenge. Researchers have come up with several ideas to ad

applicationsarxiv-cs-ai

From Proprietary to Open-Source: Bridging the Distribution Gap via Multi-Agent Protocol Distillation in Agentic Search

arXiv:2607.24280v1 Announce Type: new Abstract: Agentic search enables large language models to solve knowledge-intensive tasks by interleaving multi-step reasoning with retrieval, yet optimizing this

safetyarxiv-cs-ai

Generalization bounds and sample complexity for remaining useful life prediction from complete degradation trajectories

arXiv:2607.23454v1 Announce Type: new Abstract: Data-driven remaining useful life (RUL) prediction requires complete degradation trajectories for training, yet such run-to-failure data are scarce and

safetyarxiv-cs-lg

Grounding latent algorithm routing in transformer reasoning

model-releasesarxiv-cs-cl

arXiv:2607.24471v1 Announce Type: new Abstract: A central question in the in-context learning literature is whether transformers can organize episode-level adaptation around different inductive-bias f

Improving Adversarial Robustness of Zero-Shot CLIP with Confidence-Aware Weighting

arXiv:2510.02913v2 Announce Type: replace Abstract: Vision-language models such as CLIP demonstrate impressive zero-shot generalization but remain highly vulnerable to adversarial attacks. Prior adver

safetyarxiv-cs-cv

KANEx: Translating Kolmogorov-Arnold Networks' Interpretability to Medical Explainability

arXiv:2607.24730v1 Announce Type: cross Abstract: Computer vision models have become highly effective for medical applications, yet their black-box nature continues to undermine clinician trust. In cl

local-aiarxiv-cs-ai

KAYROS: An Anytime and Exact Open-Source Solver for Duration-Minimization Time-Dependent Vehicle Routing. A Technical Report and a Case Study in Human-AI Engineering

arXiv:2607.23116v1 Announce Type: cross Abstract: KAYROS is an open-source solver for duration-minimization time-dependent vehicle routing problems, with or without time windows (TDVRPTW, TDVRP). In t