Search: “papers”

Beyond Thinking: Imagining in 360^irc for Humanoid Visual Search

arXiv:2605.09146v1 Announce Type: new Abstract: Humanoid Visual Search (HVS) requires agents to actively explore immersive 360^irc environments. While prior methods treat this as a monolithic task rel

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BGG: Bridging the Geometric Gap between Cross-View images by Vision Foundation Model Adaptation for Geo-Localization

DGX agent

arXiv:2605.10345v1 Announce Type: new Abstract: Geometric differences between cross-view images, such as drone and satellite views, significantly increase the challenge of Cross-View Geo-Localization

model-releasesarxiv-cs-cv

12 May 2026

Bilinear autoencoders find interpretable manifolds

arXiv:2605.08891v1 Announce Type: new Abstract: Sparse autoencoders have become a standard tool for uncovering interpretable latent representations in neural networks. Yet salient concepts often span

Biological Plausibility and Representational Alignment of Feedback Alignment in Convolutional Networks

arXiv:2605.08564v1 Announce Type: new Abstract: The feedback alignment (FA) algorithm offers a biologically plausible alternative to backpropagation (BP) for training neural networks yet notably fails

safetyarxiv-cs-ai

Breaking the Reward Barrier: Accelerating Tree-of-Thought Reasoning via Speculative Exploration

arXiv:2605.10195v1 Announce Type: new Abstract: Tree-of-Thought (ToT) reasoning structures Large Language Model (LLM) inference as a tree-based search, demonstrating strong potential for solving compl

BROS: Bias-Corrected Randomized Subspaces for Memory-Efficient Single-Loop Bilevel Optimization

arXiv:2605.10288v1 Announce Type: new Abstract: Stochastic bilevel optimization (SBO) has become a standard framework for hyperparameter learning, data reweighting, representation learning, and data-m

safetyarxiv-cs-lg

CalibFree: Self-Supervised View Feature Separation for Calibration-Free Multi-Camera Multi-Object Tracking

arXiv:2605.09245v1 Announce Type: new Abstract: Multi-camera multi-object tracking (MCMOT) faces significant challenges in maintaining consistent object identities across varying camera perspectives,

Can LLMs Predict Polymer Physics Just by Reading Synthesis and Processing Prose?

model-releasesarxiv-cs-ai

arXiv:2605.08255v1 Announce Type: cross Abstract: Can large language models predict physical and mechanical polymer properties simply by reading unstructured scientific prose? Polymer performance is r

Applications

CASISR: Circular Arbitrary-Scale Image Super-Resolution

arXiv:2605.08173v1 Announce Type: new Abstract: The generalization performance (GP) of deep learning-based arbitrary-scale image super-resolution (ASISR) methods is subject to limited training dataset

applicationsarxiv-cs-cv

CausalGS: Learning Physical Causality of 3D Dynamic Scenes with Gaussian Representations

arXiv:2605.10586v1 Announce Type: new Abstract: Learning a physical model from video data that can comprehend physical laws and predict the future trajectories of objects is a formidable challenge in

tutorialsarxiv-cs-cv

CDS4RAG: Cyclic Dual-Sequential Hyperparameter Optimization for RAG

arXiv:2605.08333v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) is sensitive to the vast hyperparameters of the retriever and generator, yet optimizing them using given queries

researcharxiv-cs-ai

ChladniSonify: A Visual-Acoustic Mapping Method for Chladni Patterns in New Media Art Creation

arXiv:2605.09846v1 Announce Type: cross Abstract: In new media art creation, the mapping between vision and hearing is often subjective. As a classic carrier of sound visualization, Chladni patterns h

researcharxiv-cs-ai

Classification-Head Bias in Class-Level Machine Unlearning: Diagnosis, Mitigation, and Evaluation

arXiv:2605.08730v1 Announce Type: new Abstract: Class-level machine unlearning aims to remove the influence of specified classes while preserving model utility on retained classes. Existing methods ar

CLEAR: Context-Aware Learning with End-to-End Mask-Free Inference for Adaptive Video Subtitle Removal

arXiv:2603.21901v2 Announce Type: replace Abstract: Video subtitle removal aims to distinguish text overlays from background content while preserving temporal coherence. Existing diffusion-based metho

Coherency through formalisations of Structured Natural Language, A case study on FRETish

arXiv:2605.10462v1 Announce Type: new Abstract: Formalisation is the process of writing system requirements in a formal language. These requirements mostly originate in Natural Language. In the field

tutorialsarxiv-cs-cl

Compact SO(3) Equivariant Atomistic Foundation Models via Structural Pruning

arXiv:2605.08885v1 Announce Type: new Abstract: SO(3) equivariant graph neural networks have become the dominant paradigm for atomistic foundation models, achieving high accuracy and data efficiency b

Complex-Valued Phase-Coherent Transformer

arXiv:2605.10123v1 Announce Type: new Abstract: Complex-valued Transformers have largely inherited softmax attention from real-valued architectures. However, row-normalised token competition is not ne

Applications

Conditional anomaly detection methods for patient-management alert systems

arXiv:2605.10847v1 Announce Type: new Abstract: Anomaly detection methods can be very useful in identifying unusual or interesting patterns in data. A recently proposed conditional anomaly detection f

applicationsarxiv-cs-lg

Constraint-Aware Reinforcement Learning via Adaptive Action Scaling

arXiv:2510.11491v3 Announce Type: replace-cross Abstract: Safe reinforcement learning (RL) seeks to mitigate unsafe behaviors that arise from exploration during training by reducing constraint violati

safetyarxiv-cs-lg

Agents

Context Learning for Multi-Agent Discussion

arXiv:2602.02350v2 Announce Type: replace Abstract: Multi-Agent Discussion (MAD) has garnered increasing attention very recently, where multiple LLM instances collaboratively solve problems via struct

agentsarxiv-cs-ai

Continuum Robot Modeling with Action Conditioned Flow Matching

arXiv:2605.09216v1 Announce Type: new Abstract: Predicting the shape of tendon driven continuum robots (TDCRs) at steady state from actuation remains challenging due to continuous deformation, complex

tutorialsarxiv-cs-ro

Cool idea from Nous Research. What if you could speed up long-context pretraining with a subquadratic wrapper that you remove before deploym…

Cool idea from Nous Research. What if you could speed up long-context pretraining with a subquadratic wrapper that you remove before deployment? That is the idea behind Lighthouse Attention. The metho

tutorialsdair-ai--x

CoWorld-VLA: Thinking in a Multi-Expert World Model for Autonomous Driving

model-releasesarxiv-cs-ai

arXiv:2605.10426v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have emerged as a promising paradigm for end-to-end autonomous driving. However, existing reasoning mechanisms sti

Cross-Modal Semantic-Enhanced Diffusion Framework for Diabetic Retinopathy Grading

arXiv:2605.09242v1 Announce Type: cross Abstract: Automated grading of diabetic retinopathy (DR) faces several critical challenges: subtle inter-grade visual distinctions in fine-grained lesion patter

Cross-Sample Relational Fusion: Unifying Domain Generalization and Class-Incremental Learning

model-releasesarxiv-cs-cv

arXiv:2605.08839v1 Announce Type: new Abstract: Class-Incremental Learning (CIL) requires a learning system to learn new classes while retaining previously learned knowledge. However, in real-world sc

Crowding Out The Noise: Algorithmic Collective Action Under Differential Privacy

arXiv:2505.05707v2 Announce Type: replace Abstract: The integration of AI into daily life has generated considerable attention and excitement, while also raising concerns about automating algorithmic

safetyarxiv-cs-lg

Crystal Fractional Graph Neural Network for Energy Prediction of High-Entropy Alloys

arXiv:2605.08103v1 Announce Type: cross Abstract: High-entropy alloys (HEAs) have attracted growing attention for their exceptional mechanical and thermal properties arising from complex atomic config

local-aiarxiv-cs-ai

CTQWformer: A CTQW-based Transformer for Graph Classification

model-releasesarxiv-cs-ai

arXiv:2605.09486v1 Announce Type: cross Abstract: Graph Neural Networks (GNN) and Transformer-based architectures have achieved remarkable progress in graph learning, yet they still struggle to captur

DAPE: Dynamic Non-uniform Alignment and Progressive Detail Enhancement Techniques for Improving the Performance of Efficient Visual Language Models

arXiv:2605.08902v1 Announce Type: cross Abstract: In recent years, pre-trained visual-linguistic models have demonstrated tremendous potential, becoming a crucial foundational framework for numerous d

safetyarxiv-cs-ai

Data Mixing Can Induce Phase Transitions in Knowledge Acquisition

arXiv:2505.18091v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are typically trained on data mixtures: most data come from web scrapes, while a small portion is curated from hi

researcharxiv-cs-ai

Agents

Decentralized Contingency MPC based on Safe Sets for Nonlinear Multi-agent Collision Avoidance

arXiv:2605.10738v1 Announce Type: cross Abstract: Decentralized collision avoidance remains challenging, particularly when agents do not communicate any information related to planned trajectories. Mo

agentsarxiv-cs-ro

Decoding Islamophobic Discourse: Using LLMs to Identify Tropes and Semi-Coded Hate Speech

arXiv:2503.18273v3 Announce Type: replace Abstract: In recent years, Islamophobia has gained significant traction across Western societies, fueled by the rise of digital communication networks. This p

DeepSight: Long-Horizon World Modeling via Latent States Prediction for End-to-End Autonomous Driving

model-releasesarxiv-cs-cv

arXiv:2605.10564v1 Announce Type: new Abstract: End-to-end autonomous driving systems are increasingly integrating Vision-Language Model (VLM) architectures, incorporating text reasoning or visual rea

DegBins: Degradation-Driven Binning for Depth Super-Resolution

arXiv:2605.09628v1 Announce Type: new Abstract: Depth super-resolution (DSR) aims to recover a high-resolution (HR) depth map from its low-resolution (LR) counterpart. With color image guidance, this

Applications

Diagnosing and Mitigating Domain Shift in Permission-Based Android Malware Detection

arXiv:2605.09028v1 Announce Type: new Abstract: Machine learning-based Android malware detectors often fail in real-world deployment due to domain shift, where models trained on one data source perfor

applicationsarxiv-cs-lg

DiffATS: Diffusion in Aligned Tensor Space

arXiv:2605.09275v1 Announce Type: new Abstract: Direct diffusion modeling of high-resolution spatiotemporal fields is computationally challenging. Parameter-efficient primitives address this by repres

diffGHOST: Diffusion based Generative Hedged Oblivious Synthetic Trajectories

arXiv:2605.10647v1 Announce Type: new Abstract: Trajectories are nowadays valuable information for a wide range of applications. However they are also inherently sensitive, as they contain highly pers

tutorialsarxiv-cs-ai

Direct From Darwin: Deriving Advanced Optimizers From Evolutionary First Principles

arXiv:2605.05284v2 Announce Type: replace-cross Abstract: Evolutionary computation has long promised to deliver both high-performance optimization tools as well as rigorous scientific simulations of D

Discrete Flow Matching: Convergence Guarantees Under Minimal Assumptions

arXiv:2605.08882v1 Announce Type: new Abstract: Flow Matching has recently emerged as a popular class of generative models for simulating a target distribution mu_1 from samples drawn from a source di

DP-LAC: Lightweight Adaptive Clipping for Differentially Private Federated Fine-tuning of Language Models

arXiv:2605.10272v1 Announce Type: cross Abstract: Federated learning (FL) enables the collaborative training of large-scale language models (LLMs) across edge devices while keeping user data on-device

local-aiarxiv-cs-ai

Drift is a Sampling Error: SNR-Aware Power Distributions for Long-Horizon Robotic Planning

model-releasesarxiv-cs-ro

arXiv:2605.09537v1 Announce Type: new Abstract: Despite rapid progress in Vision-Language-Action (VLA) models for robotic control, instruction drift remains a persistent failure mode in long-horizon t

Dual Tuning for Reasoning Efficacy-Driven Data Curation in Multimodal LLM Training

arXiv:2603.04415v2 Announce Type: replace Abstract: Reasoning post-training improves Large Language Models (LLMs) on complex tasks such as mathematics and coding, but its benefits across diverse multi

tutorialsarxiv-cs-cl

Dystruct: Dynamically Structured Diffusion Language Model Decoding via Bayesian Inference

arXiv:2605.09820v1 Announce Type: new Abstract: Diffusion language models (DLMs) have recently emerged as a promising alternative to autoregressive models, primarily due to their ability to enable par

local-aiarxiv-cs-lg

EAR: Enhancing Uni-Modal Representations for Weakly Supervised Audio-Visual Video Parsing

arXiv:2605.08723v1 Announce Type: new Abstract: Weakly supervised Audio-Visual Video Parsing (AVVP) aims to recognize and temporally localize audio, visual, and audio-visual events in videos using onl

local-aiarxiv-cs-cv

EchoPrune: Interpreting Redundancy as Temporal Echoes for Efficient VideoLLMs

arXiv:2605.10050v1 Announce Type: new Abstract: Long-form video understanding remains challenging for Video Large Language Models (VideoLLMs), as the dense frame sampling introduces massive visual tok

Edit-Based Refinement for Parallel Masked Diffusion Language Models

arXiv:2605.09603v1 Announce Type: new Abstract: Masked diffusion language models enable parallel token generation and offer improved decoding efficiency over autoregressive models. However, their perf

researcharxiv-cs-cl

Hardware

Efficient Dataset Distillation for Pre-Trained Self-Supervised Models via Statistical Flow Matching

arXiv:2602.05391v2 Announce Type: replace Abstract: Dataset distillation seeks to synthesize a highly compact dataset that achieves performance comparable to the original dataset on downstream tasks.

hardwarearxiv-cs-cv

Efficient Estimation of Kernel Surrogate Models for Task Attribution

arXiv:2602.03783v2 Announce Type: replace-cross Abstract: Modern AI agents such as large language models are trained on diverse tasks -- translation, code generation, mathematical reasoning, and text

tutorialsarxiv-cs-ai