Search: “models”

AI-Augmented Thyroid Scintigraphy for Robust Classification of Disease

arXiv:2503.00366v3 Announce Type: replace-cross Abstract: Thyroid scintigraphy is vital for diagnosing thyroid disorders, yet deep learning (DL) models in this domain often struggle with limited, imba

researcharxiv-cs-cv

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Model Releases

Beyond Accuracy: Measuring Bias Acknowledgment in Chain-of-Thought Reasoning for Responsible AI Evaluation

DGX agent

arXiv:2606.15127v2 Announce Type: replace Abstract: Reasoning models are increasingly used in settings where the final answer is not the only object of review: educational tools may show students inte

model-releasesarxiv-cs-lg

23 Jun 2026

Concept Alignment Contrast and Long-Short Prompt Memory for Test-Time Adaptation of SAM3 in Medical Image Segmentation

arXiv:2606.22963v1 Announce Type: new Abstract: Concept segmentation models like Segment Anything Model 3 (SAM3) show strong generalization on natural images, yet their performance degrades in medical

safetyarxiv-cs-cv

CoRDE: Concept-Prior Routed Diffusion Experts for Structural Generalization in Robot Manipulation

arXiv:2606.21935v1 Announce Type: new Abstract: Diffusion models excel at capturing multi-modal action distributions in robot imitation learning. However, in multi-task and long-horizon scenarios, mon

CVSBench: A Comprehensive Benchmark for Cross-view Spatial Reasoning and Dreaming

arXiv:2606.22476v1 Announce Type: new Abstract: Humans can effortlessly reason about scenes across different viewpoints, yet it remains unclear whether Vision-Language Models (VLMs) possess similar cr

Data Pruning: Redundant, Problematic, and Interdependent Samples

arXiv:2606.21916v1 Announce Type: new Abstract: The performance of deep learning models is affected by not only data quantity but also data quality. Data pruning is a process by which practitioners ca

Decodable but Not Faithful: Coupling Natural-Language Rationales to Programmatic Verifiers

arXiv:2606.21678v1 Announce Type: new Abstract: Language models can generate plausible rationales for their predictions, but these explanations may not faithfully represent the model's internal reason

researcharxiv-cs-lg

Deep Learning-Based Sign Language Recognition from Videos and Cross-Lingual Translation to Indian Vernaculars

arXiv:2606.22494v1 Announce Type: cross Abstract: Sign language is a primary mode of communication for the global deaf and hard-of-hearing community, yet automated tools that recognize sign gestures f

Deep Learning for Individual Heterogeneity

arXiv:2010.14694v4 Announce Type: replace-cross Abstract: This paper integrates deep neural networks (DNNs) into structural models to increase flexibility and capture rich heterogeneity while preservi

safetyarxiv-cs-lg

Demystifying Numerical Instability in LLM Inference: Achieving Reproducible Inference for Mission-Critical Tasks with HEAL

arXiv:2606.21023v1 Announce Type: new Abstract: As Large Language Models (LLMs) deploy into mission-critical domains (e.g., finance, medicine, and law), output reproducibility has become a strict syst

DrugBench: Evaluating AI Control Protocols for Medication Harm Mitigation

arXiv:2606.20663v1 Announce Type: cross Abstract: Large Language Models have the potential to expand and improve the access to clinical information by enabling new ways of interacting with medical kno

Dynamics, stability, and energy efficiency of an energy-recycling rimless wheel with spring-clutch legs

arXiv:2606.22073v1 Announce Type: new Abstract: This paper proposes an energy-recycling rimless wheel with spring-clutch legs. The proposed mechanism uses a lockable clutch to store part of the impact

Efficient Reinforcement Finetuning via Adaptive Curriculum Learning

arXiv:2504.05520v4 Announce Type: replace Abstract: Reinforcement finetuning (RFT) has shown great potential for enhancing the mathematical reasoning capabilities of large language models (LLMs), but

safetyarxiv-cs-lg

Flowing With Purpose: Latent Action Guided Flow Matching Policies For Robotic Manipulation

arXiv:2606.23420v1 Announce Type: new Abstract: Flow matching has recently become a new standard for behavior cloning in robotic manipulation. However, state-of-the-art flow matching policies suffer f

GeoFidelity-Bench: Evaluating Segment-Level Geographic Fidelity in Text-to-Image Street-View Generation

arXiv:2606.23669v1 Announce Type: new Abstract: Text-to-image models can generate visually plausible city streets, but whether their outputs correspond to a requested road segment rather than a generi

GRAG: Generic Response-Augmented Generation Framework for Personalized Conversational Systems

arXiv:2606.21097v1 Announce Type: cross Abstract: Deploying highly capable personalized conversational agents in resource-constrained or privacy-sensitive environments remains a significant challenge.

In-Context Molecular Property Prediction with LLMs: A Blinding Study on Memorization and Knowledge Conflicts

arXiv:2603.25857v2 Announce Type: replace Abstract: The capabilities of large language models (LLMs) have expanded beyond natural language processing to scientific prediction tasks, including molecula

Introducing Mistral OCR 4. It creates structure with bounding boxes, block classification, and inline confidence scores in 170 languages. 🧵…

model-releasesarthur-mensch--x

Mistral OCR 4 is an optical character recognition model that extracts text with structural information including bounding boxes and block classification across 170 languages. The system provides inlin

Is Our Benchmark Enough? An Analysis of Continual Learning for MLLMs

arXiv:2606.20961v1 Announce Type: new Abstract: Continual adaptation is essential for multimodal large language models (MLLMs) deployed across evolving domains, but the state-of-the-art MR-LoRA method

Learning Bug Context for PyTorch-to-JAX Translation with LLMs

arXiv:2510.09898v2 Announce Type: replace Abstract: Large language models (LLMs) have shown strong performance on code translation between widely used programming languages. However, translation becom

MoECodec: Image Compression for joint human and machine perception via Mixture-of-Experts

arXiv:2606.21033v1 Announce Type: cross Abstract: Image compression for machines calls for a unified codec that serves multiple downstream vision tasks. Existing approaches either adopt task-specific

MotionHalluc: Diagnosing Kinematic Hallucinations in Fine-Grained Motion Reasoning

arXiv:2606.23061v1 Announce Type: new Abstract: Motion instruction generation in cross-video comparison aims to produce corrective feedback that describes the differences between a query and a referen

Open Problem: Is AdamW Effective Under Heavy-Tailed Noise?

arXiv:2606.23676v1 Announce Type: new Abstract: AdamW is the de facto optimizer for training large language models (LLMs), yet the theory behind it still lives mostly in finite-variance regimes. This

Physics-Guided Dual-Stream Heterogeneous Graph Neural Network for Predicting Full-Field Structural Response of Stiffened Panels

arXiv:2606.20916v1 Announce Type: new Abstract: Iterative design and optimization of large, complex structures require fast and accurate prediction of stress, displacement, and other fields. Finite el

Priority-Aware Learning-Unlearning Correction for Dynamic Decentralized LoRA Fine-Tuning

arXiv:2606.22878v1 Announce Type: new Abstract: As large language models (LLMs) are increasingly deployed at the network edge to provide pervasive generative AI services, decentralized federated learn

Revealing the Pitfalls and Re-Evaluating the Advancement of Heterophilic Graph Learning

arXiv:2409.05755v3 Announce Type: replace Abstract: Over the past decade, Graph Neural Networks (GNNs) have achieved great success on machine learning tasks with relational data. However, recent studi

RoverDevKit: An open, physics-grounded tradespace toolkit for conceptual design of lunar micro-rovers

arXiv:2606.21755v1 Announce Type: new Abstract: Pre-Phase-A design of lunar micro-rovers is dominated by tightly coupled mobility, power, thermal, and mass trades, yet conceptual-design tooling for th

S^2VG: 3D Stereoscopic and Spatial Video Generation via Denoising Frame Matrix

arXiv:2508.08048v2 Announce Type: replace Abstract: While video generation models excel at producing high-quality monocular videos, generating 3D stereoscopic and spatial videos for immersive applicat

researcharxiv-cs-cv

Self-Improvement Can Self-Regress: The Rise-and-Collapse Failure Mode of LLM Self-Training

arXiv:2606.21090v1 Announce Type: cross Abstract: Self-improvement can self-regress. In REINFORCE post-training for code, a model can quickly improve on its optimized metric and then collapse within t

Skill Coverage: A Test Adequacy Metric for Agent Skills

arXiv:2606.20659v1 Announce Type: cross Abstract: Agent skills encode reusable procedural knowledge that guides large language model agents across tasks and execution contexts. Existing evaluations pr

Local Ai

Subspace-Constrained Federated Learning with Low-Rank Adaptation

arXiv:2606.22724v1 Announce Type: new Abstract: Federated low-rank adaptation methods are attractive for fine-tuning large models under communication and privacy constraints, but heterogeneous client

local-aiarxiv-cs-lg

Temporally Aware Densification for Dynamic 3D Gaussian Splatting

arXiv:2606.23212v1 Announce Type: new Abstract: Despite modeling temporal motion, dynamic 3D Gaussian Splatting (3DGS) methods still inherit a static densification strategy that is ill-suited for dyna

Tensor Train Decomposition-based 3D Implicit Full Waveform Inversion with Multi-scale Structural Similarity

arXiv:2606.22867v1 Announce Type: cross Abstract: Three-dimensional full waveform inversion (3DFWI) is a powerful technique for reconstructing high-resolution subsurface velocity models. However, its

researcharxiv-cs-lg

The Pitfall of Scaling Up: Uncovering and Mitigating Popularity Bias Amplification in Scaling Transformer-based Recommenders

arXiv:2606.21911v1 Announce Type: cross Abstract: We identify a critical pitfall in scaling transformer-based sequential recommenders: while increasing model size improves recommendation accuracy, it

safetyarxiv-cs-lg

When AUC 0.998 Is Not Enough: A Candidate Evaluation Protocol for Hidden-State Probes of Indirect Prompt Injection in Multimodal Computer-Use Agents

arXiv:2606.22864v1 Announce Type: new Abstract: Hidden-state probing -- a linear classifier on a frozen vision-language model's internal activations -- has emerged as an attractive evaluation tool for

With agentic coding, complexity compounds in a mechanical way: unnecessary code ends up in the codebase, moves to the context window, degrad…

model-releasesfrancois-chollet--x

With agentic coding, complexity compounds in a mechanical way: unnecessary code ends up in the codebase, moves to the context window, degrades the model's reasoning abilities, leads to more unnecessar

Tools

PP-OCRv6 on Hugging Face: 50-Language OCR from 1.5M to 34.5M Parameters

PP-OCRv6 is a multilingual optical character recognition (OCR) model family released by PaddlePaddle that supports 50 languages across multiple parameter sizes ranging from 1.5M to 34.5M. The model se

toolshugging-face

22 Jun 2026

Tutorials

GLM-5.2 is great at design (Opus level IMO). I am also starting to see great results with long-running tasks, too. How is this possible? I t…

GLM-5.2 is great at design (Opus level IMO). I am also starting to see great results with long-running tasks, too. How is this possible? I think there are a few clever hacks. But I just came across th

tutorialsdair-ai--x

20 Jun 2026

Local Ai

https://huggingface.co/Lightricks/LTX-2.3-22b-IC-LoRA-Cross-Eyed Also shoutout to u/urabewe on Reddit created the content

LTX-2.3-22b-IC-LoRA-Cross-Eyed is a LoRA (Low-Rank Adaptation) model developed by Lightricks for the LTX-2.3-22b video generation model, created by Reddit user urabewe to address cross-eye artifacts i

local-aicomfyui--x

19 Jun 2026

AnchorEdit: Maintaining Temporal Consistency in Multi-turn Image Editing via Causal Memory

arXiv:2606.11751v1 Announce Type: cross Abstract: Multi-turn image editing is essential for iterative design, yet current models often struggle with identity drift and error accumulation over successi

APEX: Automated Prompt Engineering eXpert with Dynamic Data Selection

arXiv:2606.11459v1 Announce Type: cross Abstract: Large Language Models are highly sensitive to prompt formulation, necessitating automatic prompt optimization to unlock their full potential. While ev

Agents

ATLAS: Active Theory Learning for Automated Science

arXiv:2606.12386v1 Announce Type: cross Abstract: Advancing scientific understanding through mechanistic modeling requires posing the right experimental questions to yield maximally informative data.

agentsarxiv-cs-ai

Autoregressive Direct Preference Optimization

arXiv:2602.09533v2 Announce Type: replace Abstract: Direct preference optimization (DPO) has emerged as a promising approach for aligning large language models (LLMs) with human preferences. However,

researcharxiv-cs-ai

CoVR-R:Reason-Aware Composed Video Retrieval

arXiv:2603.20190v2 Announce Type: replace Abstract: Composed Video Retrieval (CoVR) aims to find a target video given a reference video and a textual modification. Prior work assumes the modification

CRUMB: Efficient Prior Fitted Network Inference via Distributionally Matched Context Batching

arXiv:2606.11473v1 Announce Type: cross Abstract: Prior-fitted networks (PFNs) are a promising class of tabular foundation models that perform in-context learning, whereby the entire labelled training

Energy-Efficient On-Device RAG on a Mobile NPU: System Design and Benchmark on Snapdragon X Elite

model-releasesarxiv-cs-cl

arXiv:2606.11257v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) pipelines are compute-intensive, combining embedding, retrieval, reranking, and large language model (LLM) generati

Exploration Structure in LLM Agents for Multi-File Change Localization

arXiv:2606.11976v1 Announce Type: cross Abstract: Software engineering tools increasingly rely on LLM based agents to localize files to change to resolve a software issue. Most AI agents explore repos