Search: “context”

Challenger at MultiPRIDE: Is It Hate Speech or Reclaimed?

arXiv:2606.01298v1 Announce Type: new Abstract: The spread of hate speech has become increasingly harmful in modern digital environments, particularly on social networking platforms. While recent adva

researcharxiv-cs-cl

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CHAM-net: A Contrastive Hierarchical Adaptive Meta-network for Robust Global Methane Flux Prediction

DGX agent

arXiv:2606.00338v1 Announce Type: new Abstract: Methane is a potent greenhouse gas that significantly contributes to global warming. However, accurately estimating global methane emissions and consump

researcharxiv-cs-lg

2 Jun 2026

ChronosAD: Leveraging Time Series Foundation Models for Accurate Anomaly Detection

arXiv:2606.01300v1 Announce Type: cross Abstract: Time series anomaly detection is a crucial task in various domains, including finance, healthcare, and industry. However, existing methods often strug

applicationsarxiv-cs-ai

Civilizational Metamaterials: Engineering Coordination Under Capability Gradients and Structural Turbulence

arXiv:2606.00235v1 Announce Type: cross Abstract: We argue that governance must transition from a normative discipline to an engineering discipline, and we develop a formal framework, inspired by the

safetyarxiv-cs-ai

ClinTutor-R1: Advancing Scalable and Robust One-to-Many Alignment in Clinical Socratic Education

arXiv:2512.05671v2 Announce Type: replace Abstract: While Large Language Models (LLMs) have achieved remarkable success in dyadic (one-on-one) instruction, they face significant challenges in One-to-M

safetyarxiv-cs-cl

CodeCytos: AI-assisted spatial molecular imaging analysis via code-augmented agent action space

model-releasesarxiv-cs-ai

arXiv:2606.00472v1 Announce Type: cross Abstract: Conventional tissue image analysis software provides foundational capabilities for cellular analysis, including segmentation, basic morphological feat

COLLAR: Cascaded Object-Level Latent Refinement for High-Fidelity Conditional Generation

arXiv:2606.00954v1 Announce Type: new Abstract: Achieving high-fidelity object-level control in Diffusion Transformers remains a significant challenge despite the introduction of structural priors lik

safetyarxiv-cs-cv

CoMIC: Collaborative Memory and Insights Circulation for Long-Horizon LLM Agents in Cloud-Edge Systems

model-releasesarxiv-cs-ai

arXiv:2606.00756v1 Announce Type: new Abstract: Deploying lightweight Large Language Model (LLM) agents on edge servers can reduce latency and move agentic services closer to users, but resource-const

Completion at the Boundary (CaB): Deployable Switching with Completion-Aware Control under Limited Calibration

model-releasesarxiv-cs-ai

arXiv:2606.00145v1 Announce Type: cross Abstract: Vision-language-action (VLA) agents can execute natural-language instructions, yet deployed systems still lack an operational interface: deciding when

Concept Heterogeneity-aware Representation Steering

arXiv:2603.02237v2 Announce Type: replace-cross Abstract: Representation steering offers a lightweight mechanism for controlling the behavior of large language models (LLMs) by intervening on internal

Constitutional Black-Box Monitoring for Scheming in LLM Agents

arXiv:2603.00829v2 Announce Type: replace-cross Abstract: Safe deployment of Large Language Model (LLM) agents in autonomous settings requires reliable oversight mechanisms. A central challenge is det

Continuous Reasoning for Vision-Language-Action

arXiv:2606.00229v1 Announce Type: cross Abstract: Natural language is a powerful reasoning medium for language and vision-language models, but it is mismatched to the granularity of continuous control

CORE-MTL: Rethinking Gradient Balancing via Causal Orthogonal Representations

arXiv:2606.02221v1 Announce Type: new Abstract: Multi-task learning (MTL) aims to construct a joint model for multiple tasks by sharing a common representation across domains. To achieve this goal, ex

CrazyMARL: Decentralized Direct Motor Control Policies for Cooperative Aerial Transport of Cable-Suspended Payloads

arXiv:2509.14126v2 Announce Type: replace Abstract: Collaborative transportation of cable-suspended payloads by teams of UAVs has the potential to enhance payload capacity, adapt to different payload

agentsarxiv-cs-ro

Local Ai

CRePE: Convolution-aware Relative Importance in Post-training Pruning with Efficient Search

arXiv:2606.01544v1 Announce Type: new Abstract: Deploying Large Language Models (LLMs) in practice incurs substantial memory and computational costs. Post-training pruning (PTP) is an effective approa

local-aiarxiv-cs-lg

Critic-R: Improving Agentic Search using Instruction-tuned Retrievers with Natural Language Introspective Feedback

arXiv:2606.00590v1 Announce Type: cross Abstract: Agentic search systems iteratively interact with retrieval models to answer complex queries. Despite substantial progress, optimizing retrievers for a

Local Ai

CryoProt: A Protein Pretraining Framework with Cross-Box Interactions on Cryo-EM Density Maps

arXiv:2606.00955v1 Announce Type: new Abstract: Despite the growing availability of cryo-electron microscopy (cryo-EM) density maps, effectively leveraging them for protein representation remains chal

local-aiarxiv-cs-lg

Data-Driven Spectral Prediction for Accelerating Large-Scale Electronic Structure Calculations

arXiv:2606.00401v1 Announce Type: cross Abstract: Simulating large molecular systems comprising thousands of atoms requires highly scalable methodologies. While modern Density Functional Theory (DFT)

Deep Learning for Generating Computational PIN-4 Immunohistochemistry Staining from Prostate Biopsy H&E Images

arXiv:2606.01871v1 Announce Type: new Abstract: Immunohistochemistry (IHC)is frequently used to resolve diagnostically ambiguous prostate cancer biopsy findings on hematoxylin and eosin (H&E)-stained

Tutorials

Deep Learning for Remote Sensing to Improve Flood Inundation Mapping

arXiv:2606.02310v1 Announce Type: new Abstract: Flooding is the most pervasive natural disaster worldwide. Timely and accurate flood inundation mapping are essential for informing disaster risk manage

tutorialsarxiv-cs-cv

DeepLatent: Think with Images via Parallel Latent Visual Reasoning

arXiv:2606.00562v1 Announce Type: new Abstract: The emerging paradigm of 'thinking with images' embeds visual states into intermediate reasoning steps, defining a new frontier for Vision-Language Mode

DiffuSent: Towards a Unified Diffusion Framework for Aspect-Based Sentiment Analysis

arXiv:2606.01323v1 Announce Type: cross Abstract: Aspect-Based Sentiment Analysis (ABSA) encompasses seven distinct subtasks, each focusing on different extracted elements. Despite the proven success

Digital Twin-Assisted Adaptive Multi-Agent DRL for Intelligent Spectrum and Resource Management in Open-RAN UAV-Enabled 6G Networks

arXiv:2606.01324v1 Announce Type: cross Abstract: The evolution toward 6G wireless networks envisions a seamlessly intelligent, Open-RAN-enabled architecture where unmanned aerial vehicles (UAVs) play

Dimension Reduction via Sum-of-Squares and Improved Clustering Algorithms for Non-Spherical Mixtures

arXiv:2411.12438v2 Announce Type: replace-cross Abstract: We develop a new approach for clustering non-spherical (i.e., arbitrary component covariances) Gaussian mixture models via a subroutine, based

Dive into Waves: Morlet Spectral Transformer for Cross-Subject Emotion Decoding from EEG

arXiv:2606.00884v1 Announce Type: cross Abstract: We study cross-subject emotion recognition from EEG, a practically important yet challenging problem in brain-computer interfaces. Unlike tasks with c

Diversity Over Frequency: Rethinking Tool Use in Visual Chain-of-Thought Agents

arXiv:2606.00096v1 Announce Type: cross Abstract: Visual agents employ external visual tools within visual chains of thought to incorporate fine-grained evidence. While prior work has mainly studied t

Do Gender Cues Affect LLM Value Trade-offs? Evidence from a Controlled Decision Benchmark

model-releasesarxiv-cs-cl

arXiv:2606.02214v1 Announce Type: new Abstract: Large language models are increasingly used in value-sensitive decision settings, where irrelevant demographic cues should not alter judgments. We const

DRL-Based Pose Control for Double-Ackermann Robots Under Actuation Uncertainties

arXiv:2606.00313v1 Announce Type: cross Abstract: Robust deployment of deep reinforcement learning (DRL) policies on real robots remains challenging due to discrepancies between simulation and real-wo

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DyLLM: Efficient Diffusion LLM Inference via Saliency-based Token Selection and Partial Attention

arXiv:2603.08026v2 Announce Type: replace-cross Abstract: Masked diffusion language models enable parallel token decoding, providing a promising alternative to the sequential nature of autoregressive

Dynamics Are Learned, Not Told: Semi-Supervised Discovery of Latent Dynamics Geometries For Zero-Shot Policy Adaptation

model-releasesarxiv-cs-ro

arXiv:2606.02280v1 Announce Type: new Abstract: Real-world dynamics shifts pose a critical challenge for reinforcement learning in robotics, as policies tightly coupled to nominal environments often f

Edge-aware Decoding for Neural Asymmetric Routing

arXiv:2606.02136v1 Announce Type: new Abstract: Neural asymmetric routing models increasingly encode directionality through matrix representations and asymmetry-aware attention. The final routing acti

Edge Prediction for Roof Wireframe Reconstruction with Transformers

arXiv:2606.02406v1 Announce Type: new Abstract: This paper presents a competitive solution to the S23DR Challenge 2026, which aims to reconstruct 3D house roof wireframe models from sparse SfM point c

EnergyMamba: An Uncertainty-Aware Graph-Enhanced Selective State Space Model for Energy Consumption Prediction

arXiv:2606.00506v1 Announce Type: new Abstract: Energy consumption prediction is essential for efficient grid management, demand-side optimization, and sustainable energy planning. Although advanced m

applicationsarxiv-cs-ai

Enhancing BiGRU with a KAN Block for Legal Document Classification and Summarization

arXiv:2606.00116v1 Announce Type: cross Abstract: This study introduces a novel architecture of KAN-based BiGRU model for the task of classification and summarization of legal documents in a low-resou

applicationsarxiv-cs-ai

EPIC: Efficient and Parallel Inference under CFG Constraints for Diffusion Language Models

arXiv:2606.00722v1 Announce Type: cross Abstract: Controlling language model outputs is essential for ensuring structural validity, reliability, and downstream usability, and diffusion language models

Evaluating Real-World Generalizability of Algorithm Selection Models

model-releasesarxiv-cs-lg

arXiv:2606.02016v1 Announce Type: new Abstract: Algorithm Selection (AS) aims to automatically identify the most suitable optimization algorithm for a given problem instance by leveraging measurable p

Evaluating the Reversal Curse in Model Editing

model-releasesarxiv-cs-cl

arXiv:2310.10322v3 Announce Type: replace Abstract: Large language models (LLMs) are prone to hallucinate unintended text due to false or outdated knowledge. Since retraining LLMs is resource intensiv

Evolving to the Aesthetics of a Vision-Language Model

arXiv:2606.00112v1 Announce Type: cross Abstract: Evolutionary systems have demonstrated remarkable results in creative domains, with recent applications in generative typography, design, and music. H

applicationsarxiv-cs-cv

ExpWeaver: LLM Agents Learn from Experience via Latent RAG

model-releasesarxiv-cs-cl

arXiv:2606.01041v1 Announce Type: new Abstract: Experience learning has achieved promising results in enhancing LLM agent planning and reasoning by integrating past interactions as reusable knowledge.

Family Matters: A Systematic Study of Spatial vs. Frequency Masking for Continual Test-Time Adaptation

arXiv:2512.08048v3 Announce Type: replace Abstract: Recent continual test-time adaptation (CTTA) methods adopt masked image modeling to stabilize learning under distribution shift, yet each treats its

safetyarxiv-cs-cv

Fast-SAM3D: 3Dfy Anything in Images but Faster

model-releasesarxiv-cs-cv

arXiv:2602.05293v2 Announce Type: replace Abstract: SAM3D enables scalable, open-world 3D reconstruction from complex scenes, yet its deployment is hindered by prohibitive inference latency. In this w

FastSLM: Hierarchical Temporal Abstraction for Efficient Long-Form Speech Adaptation

arXiv:2601.06199v3 Announce Type: replace-cross Abstract: Scaling Multimodal Large Language Models (MLLMs) to long-form speech is bottlenecked by the explosive growth of input tokens. Unlike images or

Fixed-Mean Gaussian Processes for Post-hoc Bayesian Deep Learning

arXiv:2412.04177v2 Announce Type: replace Abstract: Recently, there has been an increasing interest in performing post-hoc uncertainty estimation about the predictions of pre-trained deep neural netwo

Flexible Online Representation Learning Based on Similarity Matching

arXiv:2606.01546v1 Announce Type: new Abstract: Sparse high-dimensional representations are conducive to uncovering nontrivial structures in unsupervised exploration of data. Such a representation can

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow

model-releasesarxiv-cs-cv

arXiv:2603.28759v2 Announce Type: replace Abstract: We present FlowIt, a novel architecture for optical flow estimation that combines global matching with confidence and occlusion-guided refinement. A

FOVI: A biologically-inspired foveated interface for deep vision models

arXiv:2602.03766v2 Announce Type: replace Abstract: Human vision is foveated, with variable resolution peaking at the center of a large field of view; this reflects an efficient trade-off for active s

French parsing enhanced with a word clustering method based on a syntactic lexicon

arXiv:2606.00634v1 Announce Type: new Abstract: This article evaluates the integration of data extracted from a French syntactic lexicon, the Lexicon-Grammar (Gross, 1994), into a probabilistic parser

researcharxiv-cs-cl

Frequentist Consistency of Prior-Data Fitted Networks for Causal Inference

arXiv:2603.12037v2 Announce Type: replace Abstract: Foundation models based on prior-data fitted networks (PFNs) have shown strong empirical performance in causal inference by framing the task as an i

safetyarxiv-cs-lg