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arXiv:2606.23833v1 Announce Type: new Abstract: Terrestrial water storage (TWS) integrates snow, soil moisture, surface water, and groundwater and is a key indicator of how climate variability and hum

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Safety

Red-Teaming the Agentic Red-Team

DGX agent

arXiv:2606.24496v1 Announce Type: cross Abstract: The use of agentic systems to perform offensive security operations has moved from a theoretical possibility to a commoditized capability. However, wh

safetyarxiv-cs-ai

24 Jun 2026

REDI-Match: Rotation-Equivariant Distillation for Efficient and Robust Dense Matching

arXiv:2606.24330v1 Announce Type: new Abstract: Vision Foundation Models (VFMs) have significantly advanced dense feature matching, yet severe in-plane rotation remains a critical challenge. Existing

Reentrant value fields as delayed coupled reaction-diffusion systems on finite graphs

arXiv:2605.03940v4 Announce Type: cross Abstract: We describe a dynamical system in which a symbolic field is coupled to a geometric field via a bipartite Hilbert-Schmidt kernel. The system is fully d

researcharxiv-cs-ai

Reinforcement Learning for Computer-Use Agents with Autonomous Evaluation

arXiv:2606.24515v1 Announce Type: new Abstract: Computer-Use Agents (CUAs) execute high-level user goals by perceiving and acting directly within graphical user interfaces. However, reinforcement lear

Reinforcement Learning Towards Broadly and Persistently Beneficial Models

arXiv:2606.24014v1 Announce Type: new Abstract: As AI systems are deployed across increasingly diverse and high-stakes settings, model alignment must generalize beyond the tasks and domains seen durin

Relatively Smart: A New Approach for Instance-Optimal Learning

arXiv:2603.01346v2 Announce Type: replace Abstract: We revisit the framework of Smart PAC learning, which seeks supervised learners which compete with semi-supervised learners that are provided full k

researcharxiv-cs-lg

Agents

ReM-MoA: Reasoning Memory Sustains Mixture-of-Agents Scaling

arXiv:2606.24437v1 Announce Type: new Abstract: Mixture-of-Agents (MoA) architectures improve inference-time scaling by organizing multiple LLM agents into layered reasoning pipelines. However, existi

agentsarxiv-cs-ai

ReMMD: Realistic Multilingual Multi-Image Agentic Verification for Multimodal Misinformation Detection

arXiv:2606.24112v1 Announce Type: new Abstract: Multimodal misinformation detection is increasingly important because viral posts now combine long multilingual narratives, several images, mixed proven

Removing Noise, not Finding Gold: Quality Filtering for Large-Scale Pretraining

arXiv:2510.00866v3 Announce Type: replace-cross Abstract: Large-scale models are pretrained on massive web-crawled datasets containing documents of mixed quality, making data filtering essential. A po

researcharxiv-cs-cl

Representation Interventions Enable Lifelong Knowledge Memory Control in LLMs

arXiv:2511.20892v4 Announce Type: replace Abstract: Large language models (LLMs) often produce incorrect or outdated content after being employed. Efficient and accurate knowledge updates without cost

Rethinking Structural Anomaly Detection: From Decision Boundaries to Projection Operators

arXiv:2606.15280v2 Announce Type: replace Abstract: Most existing anomaly detection methods rely on estimating a probability density or learning an enclosing decision boundary, implicitly assuming tha

safetyarxiv-cs-lg

RetiSEM: Generalising Causal Models for Fragmented Biomedical Data

arXiv:2606.24488v1 Announce Type: cross Abstract: Learning causal models from fragmented biomedical data is challenging because clinical, molecular, and imaging variables are often incomplete or not j

Revealing Training Data Exposure in Vision Language Large Models via Parameter Gradients

arXiv:2606.24774v1 Announce Type: new Abstract: Vision-Language Large Models (VLLMs) trained on massive crawled corpora raise pressing copyright and data-provenance concerns. These concerns are partic

Reward-Centered ReST-MCTS: A Robust Decision-Making Framework for Robotic Manipulation in High Uncertainty Environments

arXiv:2503.05226v2 Announce Type: replace-cross Abstract: Monte Carlo tree search is attractive for robotic manipulation because it can improve action selection through simulation without requiring a

Agents

RIFT-Bench: Dynamic Red-teaming For Agentic AI Systems

arXiv:2606.23927v1 Announce Type: new Abstract: Agentic AI systems powered by large language models (LLMs) are rapidly evolving into autonomous decision-making systems, exposing attack vectors beyond

agentsarxiv-cs-ai

RoBoSR: Structured Scene Representations for Embodied Robotic Reasoning

arXiv:2606.24338v1 Announce Type: new Abstract: Despite rapid progress, embodied reasoning under real-world variability remains challenging. Existing approaches rely on demonstration-driven sequential

safetyarxiv-cs-ro

Robust Dual-Signal Fusion: Hybrid Neuro-Symbolic Gating with Compressed Chain-of-Thought Refinement for Irony Detection in Social Media Texts

arXiv:2606.16845v2 Announce Type: replace-cross Abstract: Small-scale Large Language Models (LLMs) natively default to literal semantic interpretations, making few-shot irony detection a persistent ch

researcharxiv-cs-ai

RoPE-Aware Bit Allocation for KV-Cache Quantization

model-releasesarxiv-cs-cl

arXiv:2606.24033v1 Announce Type: cross Abstract: Existing low-bit KV-cache quantizers often treat each cached key as a flat vector. Under RoPE, however, a key's contribution to a future attention log

RTFF: Random-to-Target Fabric Flattening Policy using Dual-Arm Manipulator

arXiv:2510.00814v2 Announce Type: replace Abstract: Robotic fabric manipulation remains challenging due to fabric deformability and occlusions from wrinkles and the manipulator. This paper defines Ran

safetyarxiv-cs-ro

Rule2Text: A Framework for Generating and Evaluating Natural Language Explanations of Knowledge Graph Rules

arXiv:2508.10971v2 Announce Type: replace-cross Abstract: Knowledge graphs (KGs) can be enhanced through rule mining; however, the resulting logical rules are often difficult for humans to interpret d

S1-Omni-Image: A Unified Model for Scientific Image Understanding, Generation, and Editing

arXiv:2606.24441v1 Announce Type: new Abstract: We present S1-Omni-Image, an open-weight unified multimodal model for scientific image understanding, generation, and editing. Unlike general-purpose im

researcharxiv-cs-cv

SAFARI: Scaling Long Horizon Agentic Fault Attribution via Active Investigation

arXiv:2606.24626v1 Announce Type: new Abstract: As autonomous agents tackle increasingly complex multi-step, multi-agent tasks, their execution trajectories have scaled beyond the constraints of even

Safe and Generalizable Hierarchical Multi-Agent RL via Constraint Manifold Control

arXiv:2606.24010v1 Announce Type: new Abstract: Multi-agent systems are widely used in safety-critical applications that require coordinated behavior under strict safety constraints. Existing approach

Same Lesson, Different Story: Cross-Lingual Reconstruction of Cultural Narratives in Large Language Models

arXiv:2606.24610v1 Announce Type: new Abstract: The evaluation of cultural grounding context becomes complex when multiple cultures convey the same moral lesson. This challenge is particularly relevan

researcharxiv-cs-cl

Applications

Sat2City v2: Native 3D City Asset Generation from a Single Satellite Image

arXiv:2606.24138v1 Announce Type: new Abstract: Generating explicit 3D city assets from a single satellite image is important for digital twins, urban simulation, and geospatial intelligence. Unlike s

applicationsarxiv-cs-cv

SC3-Eval: Evaluating Robot Foundation Models via Self-Consistent Video Generation

arXiv:2606.18610v2 Announce Type: replace-cross Abstract: Evaluating generalist robot manipulation policies in the real world is expensive, slow, and difficult to scale. Action-conditioned video world

safetyarxiv-cs-cv

ScaleToT: Generalizing Structured LLM Reasoning for Billion-Scale Low-Activity User Modeling

arXiv:2606.24605v1 Announce Type: new Abstract: Accurate user modeling often depends on rich interaction histories, which are unavailable for billions of low-activity users. Large Language Models (LLM

Applications

Scaling Laws for Task-Specific LLM Distillation

arXiv:2606.24747v1 Announce Type: new Abstract: Large Language Models (LLMs) achieve strong performance across a growing range of domains, yet their scale poses deployment challenges in applications w

applicationsarxiv-cs-ai

SciZoom: A Large-scale Benchmark for Hierarchical Scientific Summarization across the LLM Era

model-releasesarxiv-cs-cl

arXiv:2603.16131v2 Announce Type: replace Abstract: The explosive growth of AI research has created unprecedented information overload, increasing the demand for scientific summarization at multiple l

SEAGAN: domain-Specific and Edge-Aware Graph Attention Network for Dynamic Plant Processes

model-releasesarxiv-cs-lg

arXiv:2606.19623v2 Announce Type: replace Abstract: Graph neural networks (GNNs) offer a flexible framework for learning from scientific data with physical, biological, or functional associations. One

SEAL: Searching Expandable Architectures for Incremental Learning

arXiv:2505.10457v3 Announce Type: replace-cross Abstract: Incremental learning is a machine learning paradigm where a model learns from a sequential stream of tasks. This setting poses a key challenge

Segmentation and Classification of Pap Smear Images for Cervical Cancer Detection Using Deep Learning

arXiv:2508.17728v2 Announce Type: replace Abstract: Cervical cancer remains a significant global health concern and a leading cause of cancer-related deaths among women. Early detection through Pap sm

researcharxiv-cs-cv

Selective Capability Unlearning in End-to-End Spoken Language Understanding

arXiv:2606.24063v1 Announce Type: cross Abstract: Modern spoken language understanding (SLU) systems are increasingly deployed in real-world settings, where specific functionalities may need to be rem

Self-Recognition Finetuning can Prevent and Reverse Emergent Misalignment

arXiv:2606.23700v1 Announce Type: cross Abstract: Emergent misalignment (EM) has been linked to the activation of misaligned persona vectors and evil character traits, suggesting that EM operates thro

Applications

SemChunk-C: Semantic Segmentation for C Code

arXiv:2606.23697v1 Announce Type: cross Abstract: Semantic segmentation of code written in a C-family language remains a challenging problem, due to the language's complex syntax, macro expansion, and

applicationsarxiv-cs-ai

Sentence-Level Contextual Entrainment in Large Language Models

arXiv:2606.24077v1 Announce Type: new Abstract: Contextual entrainment, which is a newly discovered phenomenon in large language models (LLMs), refers to the tendency of a model to assign higher proba

researcharxiv-cs-cl

Local Ai

SENTRY: SAM2-Enhanced Neighbor-Aware and Temporally Reasoned Memory for Visual Tracking

arXiv:2606.24449v1 Announce Type: new Abstract: We revisit the memory update mechanism in SAM2-based visual object tracking and identify confidence-only mask selection as the dominant cause of drift u

local-aiarxiv-cs-cv

Separating Oblivious and Adaptive Models of Variable Selection

arXiv:2602.16568v2 Announce Type: replace-cross Abstract: Sparse recovery is among the most well-studied problems in learning theory and high-dimensional statistics. In this work, we investigate the s

researcharxiv-cs-lg

SER: Learning to Ground Video Reasoning with Semantic Evidence Rewards

arXiv:2606.24726v1 Announce Type: new Abstract: Video MLLMs often struggle with fine-grained spatio-temporal reasoning, sometimes generating correct answers based on irrelevant frames or objects. Alth

Sesame: Structure-Aware Molecular Generation via Spatial Density-Map Conditioning

arXiv:2606.23856v1 Announce Type: new Abstract: Generative molecular models for drug design are a promising direction with much active research. In the next phase of computational drug design, such mo

researcharxiv-cs-lg

Sexualised synthetic personas encode and amplify gendered power asymmetries through voice

arXiv:2606.21366v2 Announce Type: replace-cross Abstract: This work examines sexualised AI-generated English-speaking voices offered by a popular commercial platform. New technologies may enable sexua

researcharxiv-cs-ai

Local Ai

SHERLOC: Structured Diagnostic Localization for Code Repair Agents

arXiv:2606.24820v1 Announce Type: new Abstract: LLM agents solve repository-level coding tasks through multi-turn tool use, but utilize half their budget on locating faults before editing. Dedicated l

local-aiarxiv-cs-cl

SICI: A Semantic-Pragmatic Complexity Index Reveals Regime Shifts in LLM Stance Detection

model-releasesarxiv-cs-cl

arXiv:2606.13189v2 Announce Type: replace Abstract: Prompt-based LLMs are increasingly used for stance detection, but harder examples are not always repaired by clearer instructions, reasoning prompts

SignNet-1M: Large-Scale Multilingual Sign Language Video Dataset with Downstream Benchmarks

arXiv:2606.24361v1 Announce Type: new Abstract: Sign language models are typically trained on datasets captured under constrained conditions, with limited viewpoint, background, and signer-identity di

Sim-to-Real Betting on the E-Process: Bringing 'simulators' to anytime-valid confidence sequences

arXiv:2606.24038v1 Announce Type: new Abstract: This note describes an integration of the sim-to-real performance estimate with betting (from Chen et al.) and the safe anytime-valid inference (from Ra

researcharxiv-cs-ro

Similarity of Neural Network Representations in Superposition

arXiv:2604.00208v2 Announce Type: replace Abstract: Comparing internal representations is a central goal in neuroscience and machine learning, but standard linear alignment metrics (Representational S

safetyarxiv-cs-lg

Agents

Skills for the future software profession: beyond agentic AI!

arXiv:2606.21894v2 Announce Type: replace-cross Abstract: As coding agents are rapidly changing software engineering, a natural question is: what are the core skills needed by future software engineer

agentsarxiv-cs-ai