Search: “models”

From Detecting Agency to Doing Work: Self-Caused Credit Builds a Durable Behavioral Self in a Minimal Spiking Agent

arXiv:2606.30191v1 Announce Type: new Abstract: How does an agent that can tell self from world come to be durably shaped by that distinction? Recent work shows that a predictive system can detect its

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From Fog Chamber to Aircraft Window: Pixel-Registered Imaging and Synthetic Fine-Tuning Enable Cross-Domain Defogging

DGX agent

arXiv:2606.29093v1 Announce Type: new Abstract: A deep defogging pipeline pretrained on controlled laboratory fog and fine-tuned with domain-randomized synthetic fog applied to clear outdoor scenes ge

model-releasesarxiv-cs-cv

30 Jun 2026

From Regulatory Approvals to Patents: Cross-Domain Linking for Cardiovascular Device Traceability

arXiv:2606.28353v1 Announce Type: cross Abstract: Linking FDA-approved medical devices to their underlying United States Patent and Trademark Office (USPTO) patents enables critical applications such

GeoEdit: Geometry-Aware Object Editing via Dual-Branch Denoising

model-releasesarxiv-cs-cv

arXiv:2606.30003v1 Announce Type: new Abstract: Precisely manipulating objects in a single photograph (translation, rotation, scaling) while obeying 3D physical constraints remains unsolved for diffus

Geometric Measurements of the Axiom of Choice in Neural Proof Embeddings

arXiv:2606.28572v1 Announce Type: cross Abstract: The axiom of choice has divided the foundations of mathematics for over a century, but the distinction between classical and constructive proofs has r

Local Ai

GLIP: Graph and LLM Joint Pretraining for Graph-Level Tasks

arXiv:2606.29773v1 Announce Type: new Abstract: Graphs are widely used to model relational systems, with applications in domains such as social networks, finance, and biomedicine. Graph neural network

local-aiarxiv-cs-lg

Good Enough? An Investigation on the Impact of Label Quality in Large-Scale Medical Datasets

arXiv:2505.20928v2 Announce Type: replace Abstract: Manually refining radiological segmentation masks is highly resource-intensive. To determine when this expert commitment is truly justified for the

Ground4D: Consistency-Aware 4D Reconstruction from Monocular Video

arXiv:2606.28828v1 Announce Type: new Abstract: Learning a 4D scene representation from a single monocular video that supports dynamic novel-view synthesis while maintaining faithful geometry over tim

Tutorials

Grounding LLM Reasoning under Incomplete Graph Evidence

arXiv:2606.30247v1 Announce Type: new Abstract: Knowledge graphs can guide large language models (LLMs) reasoning, but the graph seen by a system is usually a retrieved, linked, temporally scoped, and

tutorialsarxiv-cs-cl

H-GRPO: Permutation-Invariant Reinforcement Learning for Grounded Visual Reasoning

arXiv:2606.29915v1 Announce Type: new Abstract: Vision-Language Models (VLMs) often achieve high performance on benchmarks while remaining 'black boxes', yet they remain prone to hallucination or rely

Hard-constraint physics-residual networks for hydrogen crossover prediction and high-pressure extrapolation in PEM water electrolysis

arXiv:2511.05879v5 Announce Type: replace-cross Abstract: Hydrogen crossover is a critical safety and efficiency constraint in high-pressure polymer electrolyte membrane water electrolysis (PEMWE), bu

HMARS: A Hierarchical Multi-Agent Memory System for Long-Context Reasoning

arXiv:2606.28349v1 Announce Type: cross Abstract: Long-context reasoning requires models to access, retrieve, and integrate evidence scattered across documents, dialogues, and accumulated interaction

How Far Can Sharpness and Complexity Jointly Explain Generalization?

arXiv:2606.29043v1 Announce Type: new Abstract: Sharpness and complexity are two central factors in the generalization analysis of deep neural networks. Existing quantitative evaluations of generaliza

HyBIRD: Hyperbolic Bridge Retrieval and Diagnosis for Methodology Inspiration Retrieval

arXiv:2606.28336v1 Announce Type: cross Abstract: Methodology Inspiration Retrieval (MIR) asks a system to retrieve prior papers whose methods can inspire a new research proposal. Unlike general scien

Applications

HyPER-GAN: Hybrid Patch-Based Image-to-Image Translation for Real-Time Photorealism Enhancement in Game Engines

arXiv:2603.10604v3 Announce Type: replace Abstract: Generative models are increasingly used in video game engines to enhance the photorealism of rendered images for visual synthetic data generation an

applicationsarxiv-cs-cv

IBRSteG: Learning a Generalizable Steganography Framework for 3D Gaussian Splatting

arXiv:2606.30024v1 Announce Type: cross Abstract: Recent advances in deep learning have notably improved steganographic message hiding. However, designing a generalizable steganographic approach for 3

IHDec: Divergence-Steered Contrastive Decoding for Securing Multi-Turn Instruction Hierarchies

arXiv:2606.29960v1 Announce Type: new Abstract: Large Language Models (LLMs) often fail to maintain instruction hierarchies (IH) when processing multi-source inputs with varying role-level priorities,

safetyarxiv-cs-cl

Inference-time optimization for experiment-grounded protein ensemble generation

arXiv:2602.24007v3 Announce Type: replace-cross Abstract: Protein function relies on dynamic conformational ensembles, yet current generative models like AlphaFold3 often fail to produce ensembles tha

safetyarxiv-cs-lg

KbSD: Knowledge Boundary aware Self-Distillation for Behavioral Calibration in Agentic Search

arXiv:2606.29863v1 Announce Type: new Abstract: Agentic search equips large language models with dynamic retrieval abilities, but existing reinforcement learning methods remain limited by reward spars

agentsarxiv-cs-cl

LC-ICL: Label-Guided Contrastive In-Context Learning for Robust Information Extraction

arXiv:2606.29407v1 Announce Type: cross Abstract: There has been increasing interest in exploring the capabilities of advanced large language models (LLMs) in the field of information extraction (IE),

researcharxiv-cs-ai

Learning from samples: inverse problems over measures

arXiv:2505.07124v3 Announce Type: replace Abstract: We study inverse problems where an unknown potential is observed only through samples from the measure it induces by a convex variational principle.

Learning to Bid in Discriminatory Auctions with Budget Constraints

arXiv:2606.29252v1 Announce Type: new Abstract: We study repeated bidding in multi-unit discriminatory (pay-as-bid) auctions for a single bidder with per-round utility equal to value minus alpha times

LLM-Guided Planning for Multi-hop Reasoning over Multimodal Nuclear Regulatory Documents

arXiv:2606.29399v1 Announce Type: new Abstract: Reviewing nuclear regulatory documents requires multi-hop reasoning across tens of thousands of pages, where judgments depend on evidence assembled acro

LLM Serving Optimization with Variable Prefill and Decode Lengths

arXiv:2508.06133v4 Announce Type: replace-cross Abstract: We study offline scheduling for large language model (LLM) serving under a fixed KV-cache memory budget, where requests have heterogeneous pro

researcharxiv-cs-ai

Applications

LLMography: Transforming Human-AI Conversations into Traceability, Oversight, and Auditability Indicators

arXiv:2606.29437v1 Announce Type: cross Abstract: The growing use of Large Language Models (LLMs) in education, software engineering, academic writing, and technical documentation raises a key questio

applicationsarxiv-cs-ai

MaDI-Bench: An End-to-End Data Integration Benchmark

model-releasesarxiv-cs-cl

arXiv:2606.30371v1 Announce Type: cross Abstract: Data integration combines heterogeneous data sets into a single, coherent representation. Data integration involves a sequence of interdependent tasks

mamabench and mamaretrieval: Benchmarks for Evaluating Medical Retrieval-Augmented Generation in Maternal, Neonatal, and Reproductive Health

model-releasesarxiv-cs-cl

arXiv:2606.29467v1 Announce Type: new Abstract: Medical question-answering benchmarks rarely cover the maternal, neonatal, child, and reproductive-health questions a nurse-midwife asks, and, to our kn

ManimAgent: Self-Evolving Multimodal Agents for Visual Education

arXiv:2606.30296v1 Announce Type: new Abstract: Multi-round reflection lets agents built on large language models recover from failures within a single task, but each task remains an isolated episode:

MARS: A neurosymbolic approach for interpretable drug discovery

arXiv:2410.05289v4 Announce Type: replace Abstract: Background: Neurosymbolic (NeSy) artificial intelligence describes the combination of logic or rule-based techniques with neural networks. Compared

safetyarxiv-cs-ai

MAVIN: Multi-Shot Audio-Visual Generation with Narrative Control

arXiv:2606.29473v1 Announce Type: new Abstract: While recent generative models produce high-fidelity videos, they struggle with the complex narrative control required for coherent multi-shot audio-vis

agentsarxiv-cs-cv

MemLeak: Diagnosing Information Leaks in Multimodal Agent Memory

arXiv:2606.29788v1 Announce Type: new Abstract: When a multimodal AI agent is asked to forget a fact, current memory systems usually delete the text entry and report success. We find that the fact can

Meta-learning as a principle for human-like visual representations

arXiv:2606.28399v1 Announce Type: new Abstract: The structure of human visual representations underpins our capacity for adaptive behaviour. While pretrained neural networks model human visual represe

safetyarxiv-cs-cv

MIThinker: A Plug-and-Play Policy-Optimized Thinker For Motivational Interviewing Counseling

arXiv:2606.29265v1 Announce Type: new Abstract: Reasoning large language models (LLMs) have recently made much progress in complex problem-solving, leveraging internal reasoning (or thought) to guide

safetyarxiv-cs-cl

Mitigating the Safety-utility Trade-off in LLM Alignment via Adaptive Safe Context Learning

arXiv:2602.13562v2 Announce Type: replace-cross Abstract: While reasoning models have achieved remarkable success in complex reasoning tasks, their increasing power necessitates stringent safety measu

safetyarxiv-cs-ai

Monte Carlo Energy Aggregation for Mobile 3D Gaussian Splatting

model-releasesarxiv-cs-cv

arXiv:2606.30017v1 Announce Type: new Abstract: Recent advances in 3D Gaussian Splatting have demonstrated unprecedented success in novel view synthesis. However, the substantial inference and storage

Multi-Agent Route Planning as a QUBO Problem

model-releasesarxiv-cs-ro

arXiv:2602.07913v2 Announce Type: replace Abstract: Multi-Agent Route Planning considers selecting vehicles, each associated with a single predefined route, such that route-level coverage utility is m

Multi-Class Human/Object Detection on Robot Manipulators using Proprioceptive Sensing

arXiv:2508.02425v2 Announce Type: replace-cross Abstract: In physical human-robot collaboration (pHRC) settings, humans and robots collaborate directly in shared environments. Robots must analyze inte

safetyarxiv-cs-ai

Multiply Robust Causal Mediation Analysis with Continuous Treatments

arXiv:2105.09254v4 Announce Type: replace-cross Abstract: In many applications, researchers are interested in the direct and indirect causal effects of a treatment or exposure on an outcome of interes

Muon learns balanced solutions in matrix factorization without slow saddle-to-saddle dynamics

arXiv:2606.30509v1 Announce Type: new Abstract: Matrix factorization (i.e., problems of the form min_{mathbf{P},mathbf{Q}} |mathbf{M}^star - mathbf{P}^opmathbf{Q}|_F^2) is a minimal learning problem t

Neural Procedural Memory: Empowering LLM Agents with Implicit Activation Steering

arXiv:2606.29824v1 Announce Type: cross Abstract: While Large Language Models (LLMs) excel as static solvers, transforming them into autonomous agents remains challenging. This transition requires con

Neural Subspace Reallocation: Continual Learning as Retrieval-Based Subspace Memory Management

arXiv:2606.30067v1 Announce Type: cross Abstract: We introduce Neural Subspace Reallocation (NSR), which reframes continual learning as memory management over parameter subspaces. Instead of treating

On the Necessity of a Liquid Substrate for Mesh Intelligence

arXiv:2606.28413v1 Announce Type: cross Abstract: A mesh of sovereign agents has no center: no shared clock, no shared model, and no coordinator to gather data or retrain. Its competence rests on each

On the Policy Gradient Foundations of Group Relative Policy Optimization: Credit Assignment, Gradient Sparsity, and Rank Collapse

arXiv:2606.29238v1 Announce Type: new Abstract: Group Relative Policy Optimization (GRPO) eliminates the learned critic in PPO by using the mean reward of grouped rollouts as a baseline. We provide a

Local Ai

Online Data Selection for Instruction Tuning via Gaussian Processes

arXiv:2606.30077v1 Announce Type: cross Abstract: With Large Language Model (LLM) pre-training and fine-tuning shifting its focus from data volume to data quality, quality data selection has emerged a

local-aiarxiv-cs-ai

Optimization Dynamics Imprint Semantic Specificity in Contrastive Embedding Norms

arXiv:2606.30625v1 Announce Type: cross Abstract: Contrastive embedding models trained with scale-invariant losses are typically paired with distance metrics like cosine similarity, effectively ignori

researcharxiv-cs-ai

OSWorld2.0: Benchmarking Computer Use Agents on Long-Horizon Real-World Tasks

arXiv:2606.29537v1 Announce Type: new Abstract: Existing computer-use benchmarks fail to capture the realism, complexity, and long-horizon demands of real-world computer use, limiting their ability to

PCGD: Physics-Guided Conditional Graph Diffusion for TCAD Device Simulation

arXiv:2606.29272v1 Announce Type: new Abstract: Technology computer-aided design (TCAD) semiconductor device simulation is fundamentally constrained by the high computational cost of iteratively solvi

Personalizing MLLMs via Reinforced Multimodal Reference Game

arXiv:2606.28845v1 Announce Type: new Abstract: Personalizing Multimodal Large Language Models (MLLMs) aims to recognize users' unique concepts from visual data and provide personalized responses. Alt