Search: “concepts”

PLRS-IC: A Dual-Calibration Framework for Chest X-Ray Vision-Language Alignment

model-releasesarxiv-cs-cv

arXiv:2609.39266v1 Announce Type: new Abstract: Fine-grained vision-language alignment in chest radiography enables zero-shot classification, grounding, and segmentation without task-specific annotati

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ReLaG: A Scalable Framework Generalizing Random Splits to Data with Latent Relations

DGX agent

arXiv:2609.38538v1 Announce Type: cross Abstract: Random splitting can yield non-independent train--test subsets when a dataset contains related samples, as is common in certain applications such as b

applicationsarxiv-cs-ai

1 Oct 2026

Searching for BSM Experimental Signatures with Large Lagrangian Models

model-releasesarxiv-cs-ai

arXiv:2609.38309v1 Announce Type: cross Abstract: The search for physics Beyond the Standard Model (BSM) is generally limited not by the supply of theory descriptions but by the lack of discriminating

ShieldCLIP: Selective Safety Alignment for Harmful Content Mitigation in Multimodal Foundation Models

arXiv:2609.39688v1 Announce Type: cross Abstract: Multimodal encoders such as CLIP underlie many downstream systems, but their web-scale training data embed harmful associations that safety alignment

Local Ai

Steering Fields: Adaptive Vector Fields for Safe Image Generation and Beyond

arXiv:2609.39573v1 Announce Type: cross Abstract: As state-of-the-art text-to-image flow models achieve near-photorealistic quality, controlling their outputs, e.g., suppressing harmful content while

local-aiarxiv-cs-ai

Agents

Survival is the Only Reward: Sustainable Self-Training Through Environment-Mediated Selection

arXiv:2601.12310v2 Announce Type: replace Abstract: Self-training systems often degenerate due to the lack of an external criterion for judging data quality, leading to reward hacking and semantic dri

agentsarxiv-cs-ai

The Missing Coefficients: Bayesian Pairwise Merging for Model Personalization

arXiv:2609.39055v1 Announce Type: new Abstract: How can we personalize a shared expert library from a user's pairwise choices? Prior work can realize different reward trade-offs by merging reward-spec

Local Ai

Towards Model as a Library: Offline, Community-Sourced AI for Low-Resource African Languages

arXiv:2609.38574v1 Announce Type: new Abstract: Large language models are frequently proposed as a route to AI-powered services for African communities, but they are least reliable exactly where the n

local-aiarxiv-cs-ai

Understanding Parents' Complex Views of AI for Children's Pretend Play

arXiv:2609.39906v1 Announce Type: cross Abstract: AI could support children's pretend play, but it could also direct the play on behalf of children. Whether AI should have roles in children's lives is

A Proposed Rubric for Evaluating Expressed Clinical Reasoning in Large Language Model Responses

arXiv:2609.37788v1 Announce Type: cross Abstract: Rubrics support the structured evaluation of language models. We propose a rubric for assessing expressed clinical reasoning in model responses, drawi

ADMM-based Continuous Trajectory Optimization in Graphs of Convex Sets

arXiv:2603.11335v2 Announce Type: replace Abstract: This paper presents a numerical solver for computing continuous trajectories in non-convex environments. Our approach relies on a customized impleme

researcharxiv-cs-ro

Cheap to Hypothesize, Costly to Verify: The Defense Surface of Agentic Vulnerability Discovery

model-releasesarxiv-cs-ai

arXiv:2609.35909v1 Announce Type: cross Abstract: Autonomous LLM agents turn vulnerability discovery into a repository-scale search: they generate many vulnerability hypotheses but can verify only a s

Codebook-Guided Cross-Modal Knowledge Distillation for Structurally Heterogeneous Features

arXiv:2609.37243v1 Announce Type: cross Abstract: Cross-modal knowledge distillation transfers knowledge from a teacher modality to a student modality. Existing feature-level alignment methods typical

Cropland PAtteRNS: Parallel Dimensional Attention Networks and Attention to Dataset Disparity for Crop Segmentation in Satellite Imagery Time Series Data

arXiv:2609.38165v1 Announce Type: new Abstract: The landscape of satellite imagery time series datasets and boundary-pushing architectures for cropland segmentation has never been richer. However, in

researcharxiv-cs-cv

Evaluating the Evaluators: Diagnosing Large Multimodal Models for AI-Generated Image Assessment

model-releasesarxiv-cs-cv

arXiv:2609.37576v1 Announce Type: new Abstract: With the rapid advancement of text-to-image (T2I) generation, robust evaluation becomes critical yet challenging, as traditional metrics fail to capture

From Neurons to Conversation: Speech Brain-Computer Interfaces

arXiv:2609.36736v1 Announce Type: cross Abstract: Speech brain-computer interfaces (BCIs) aim to restore communication by transforming neural activity related to speech, language, or communicative int

researcharxiv-cs-cl

From Sky to Soil: A Morphing Aerial-Ground Robot for Seed Deployment

arXiv:2609.37072v1 Announce Type: new Abstract: Aerial seed broadcasting can reach remote restoration sites, but provides limited control over seed placement within the soil. This paper presents a geo

researcharxiv-cs-ro

Generated Query Expansion Still Helps Strong Sparse Retrieval: A Controlled Study with SPLADE-v3

arXiv:2609.37911v1 Announce Type: cross Abstract: Scientific queries are often brief, while relevant papers use specialized vocabulary. Generated query expansion can bridge this mismatch, but earlier

Learning to Harvest Without Collapse in a Regenerative Commons: A Lagrangian Framework

arXiv:2609.36478v1 Announce Type: new Abstract: The tragedy of the commons poses a multi-agent safety problem: reward-seeking agents can deplete a shared resource, and cooperation among its users does

Making Cross-Continental Federated Learning Repeatable with FLIP: a Multi-Application Study

arXiv:2609.36001v1 Announce Type: cross Abstract: Federated learning (FL) in healthcare remains challenging, as the overhead of rebuilding governance guarantees for every collaboration stops most proj

applicationsarxiv-cs-cv

MSTypography: Multi-character Semantic Typography via Balancing Word Legibility and Object Recognizability

arXiv:2609.37141v1 Announce Type: new Abstract: Semantic typography is a design technique where the visual representation of a word conveys its semantic meaning, while maintaining its legibility. Exis

researcharxiv-cs-cv

On Task Scope and Information Retention in Source Coding

arXiv:2609.37575v1 Announce Type: cross Abstract: We argue that dividing codec design into Coding for Machines (CfM) and Coding for Humans (CfH) is a misleading distinction for deciding what informati

Online Versatile Incremental Learning: Towards Class and Domain-Agnostic Adaptation at Any Time

arXiv:2609.36442v1 Announce Type: cross Abstract: Continual learning enables vision systems to adapt to ever-changing data distributions. Despite significant advances, existing approaches fail to capt

applicationsarxiv-cs-ai

Phaedra: Learning High-Fidelity Discrete Tokenization for the Physical Science

arXiv:2602.03915v2 Announce Type: replace-cross Abstract: Tokens are discrete representations that allow modern deep learning to scale by transforming high-dimensional data into sequences that can be

applicationsarxiv-cs-ai

ReCAP: Retrieval-Guided Capability Reuse for Multimodal Continual Instruction Tuning

model-releasesarxiv-cs-cv

arXiv:2609.37889v1 Announce Type: new Abstract: Multimodal continual instruction tuning (MCIT) aims to enable multimodal large language models to acquire new capabilities from sequential tasks while p

Released Wulver v0.5, our Krea 2 finetune for anime and furry.

model-releasesr-stablediffusion

Wulver v0.5 is a full fine-tune of Krea 2 Raw (the whole 12.8B DiT) for anime and anthro characters, including scenes where several characters interact. We made it at Vaelico, an independent studio. C

Sequence Variables: A Constraint Programming Computational Domain for Routing and Sequencing

arXiv:2510.09373v2 Announce Type: replace Abstract: Constraint Programming (CP) offers an intuitive, declarative framework for modeling Vehicle Routing Problems (VRP). While classical successor-based

Spanner Omni, now GA: A distributed, multi-model database that you can deploy anywhere

model-releasesgoogle-cloud-ai

Spanner Omni, the deploy-anywhere version of Spanner, is now generally available, ready to power your most demanding production workloads in your on-premises data center or on other clouds. With Spann

TRACE: Deployable Tree-Relational Structure Enhancement for Oncology LLMs

model-releasesarxiv-cs-ai

arXiv:2609.35810v1 Announce Type: cross Abstract: Large language models are increasingly used in oncology applications, but their predictions are often weakly grounded in explicit medical structure. W

Using AFM 3 PCC as an alternative to Local LLM

Apple Foundation Model 3 through Private Cloud Compute is directly available in macOS 27.2 through familiar AI clients. For Mac users running local models such as Qwen 3.x or Gemma 4, AFM 3 PCC is a c

model-releasesr-ollama

Vulnerability Discovery and Exploitation Trends in the AI Era

model-releasesgoogle-cloud-ai

Written by: Robin Grunewald, Supriya Mazumdar, Kelli Vanderlee Introduction Google Threat Intelligence Group (GTIG) examines vulnerability disclosure and exploitation statistics to evaluate the impact

Which Attention Heads are like the Human Head? Not the Ones that Compute

arXiv:2609.37991v1 Announce Type: new Abstract: Brain-AI alignment is often interpreted as a sign that model and brain perform similar computations. Whether the aligned units are causally involved in

A Unified Uncertainty Representation for Graph Neural Networks via Doubly-Spectral Stochastic Expansion

arXiv:2609.35703v1 Announce Type: new Abstract: Reliable deployment of graph neural networks requires calibration, out-of-distribution (OOD) detection, and robustness to distribution shift, yet existi

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

Beyond Saying Less: Fine-Grained Alignment for Informative and Faithful Vision-Language Models

arXiv:2609.35294v1 Announce Type: new Abstract: Object hallucination remains a major challenge for large vision-language models. While off-policy preference optimization proves to be an effective solu

safetyarxiv-cs-cv

Can Attack Difficulty Be Characterized Before Optimization? A Study of Pre-optimization Difficulty in Person-Vanishing Attacks

arXiv:2609.34501v1 Announce Type: new Abstract: Adversarial attacks against object detectors are traditionally studied from an optimization perspective, where attack difficulty is regarded as an outco

researcharxiv-cs-cv

From Dual Tracking to Clipping: Provably Faster Distributionally Robust Multi-Objective Optimization

arXiv:2605.05660v2 Announce Type: replace Abstract: Multi-objective optimization (MOO) has received growing attention in applications that require learning under multiple criteria. However, most exist

From Scores to Samples: Elastic Forcing for Autoregressive Video Generation

arXiv:2609.35491v1 Announce Type: new Abstract: Few-step autoregressive video generation commonly relies on Distribution Matching Distillation (DMD), requiring a bidirectional diffusion teacher and an

safetyarxiv-cs-cv

Less Sycophancy, Stronger Refusal? Lessons for AI Safety from Mechanistic Interpretability

arXiv:2609.35544v1 Announce Type: cross Abstract: Reliable refusal of harmful requests is essential to the safe deployment of language models. Because excessive eagerness to please users may undermine

LFPO: Likelihood-Free Policy Optimization for Masked Diffusion Models

arXiv:2603.01563v2 Announce Type: replace Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has achieved remarkable success in improving autoregressive models, especially in domains requ

Notes on Generative Modeling for Feedback Control and Planning

arXiv:2609.33164v1 Announce Type: cross Abstract: In these notes, we view control as a dynamically constrained sampling problem on the state-space of a control system. With this viewpoint, we extend m

Local Ai

OOD Generalization as a Bifurcation Problem

arXiv:2609.33562v1 Announce Type: new Abstract: Systematic out-of-distribution (OOD) generation remains a critical bottleneck for continuous-time generative models. While standard joint classifier-fre

local-aiarxiv-cs-lg

Agents

Recent Advances in Agentic Agri-Robotic Phenotyping: A Perspective Review from Fragmented Multimodal Sensing to Unified PhenoAgent Intelligence

arXiv:2609.34567v1 Announce Type: new Abstract: This review examines the evolution of plant phenotyping from conventional manual trait measurement to high-throughput, robotic, and artificial intellige

agentsarxiv-cs-cv

Self-eXplainable AI for Medical Image Analysis: A Survey and New Outlooks

arXiv:2410.02331v3 Announce Type: replace Abstract: The increasing demand for transparent and reliable models, particularly in high-stakes decision-making areas such as medical image analysis, has led

applicationsarxiv-cs-cv

Training-Free Uncertainty Estimation for Embedding Models

arXiv:2306.00206v3 Announce Type: replace Abstract: Embedding models, often obtained via self-supervised learning, extract general-purpose representations from data. Quantifying the reliability of the

A Safety-Bounded SDC-to-MCP Gateway for Medical AI Agents

arXiv:2609.31358v1 Announce Type: cross Abstract: The Model Context Protocol (MCP) provides a common interface through which AI applications discover and use external resources and tools. It allows la

28 Sept 2026

A Synthetic Ground-Truth Framework for the Evaluation of Explainable AI Methods

arXiv:2609.30397v1 Announce Type: new Abstract: Evaluating explainable Artificial Intelligence (XAI) methods is a challenging task due to the lack of reliable evaluation procedures and, in particular,

28 Sept 2026

Actively Resolving Contextual Uncertainty for Underspecified Tasks in Natural Language

arXiv:2609.30428v1 Announce Type: cross Abstract: Foundation models provide robots with the ability to interpret natural language and reason about environmental context, yet most language-conditioned