model releases

RAW: Robust Avatar Watermarking -- Benchmarking and Baseline

arXiv:2605.23994v1 Announce Type: cross Abstract: Digital avatar watermarking presents unique challenges: avatars are routinely post-processed with background replacement, reframing, and format conver

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READER: Reasoning-Enhanced AI-Generated Text Detection

DGX agent

arXiv:2605.25281v1 Announce Type: cross Abstract: Recent advances in large language models (LLMs) have made it increasingly difficult to distinguish human-written text from AI-generated content. Many

model-releasesarxiv-cs-ai

26 May 2026

RealBench: Benchmarking Data-Driven Numerical Weather Forecasting Under Operational Conditions and Extreme Event Challenges

arXiv:2605.24945v1 Announce Type: cross Abstract: Accurate evaluation of weather forecasting models is critical for their reliable deployment in real-world applications. However, existing benchmarks p

RECTOR: Priority-Aware Rule-Based Reranking for Compliance-Aware Autonomous Driving Trajectory Selection

arXiv:2605.25095v1 Announce Type: new Abstract: Autonomous driving stacks must pick one trajectory from a multi-modal candidate set; choosing by model confidence ignores safety, traffic-law, and comfo

RED: Adaptive Real-Time DAG Scheduling for Robotic Inference under Environmental Dynamics

arXiv:2605.24044v1 Announce Type: new Abstract: Robots deployed in dynamic environments must contend with environment-driven changes that reshape computation at runtime: new tasks may appear, preceden

Red-Teaming Claude Opus and ChatGPT-based Security Advisors for Trusted Execution Environments

arXiv:2602.19450v2 Announce Type: replace-cross Abstract: Trusted Execution Environments (TEEs) (e.g., Intel SGX and ArmTrustZone) aim to protect sensitive computation from a compromised operating sys

Refining Context-Entangled Content Segmentation via Curriculum Selection and Anti-Curriculum Promotion

arXiv:2602.01183v2 Announce Type: replace-cross Abstract: Biological learning proceeds from easy to difficult tasks, gradually reinforcing perception and robustness. Inspired by this principle, we add

Reflect-Guard: Enhancing LLM Safeguards against Adversarial Prompts via Logical Self-Reflection

arXiv:2605.24834v1 Announce Type: cross Abstract: Large language model (LLM) safety classifiers such as Llama Guard are effective at detecting overtly harmful prompts but remain vulnerable to adversar

Reinforcement Learning for Laser Additive Manufacturing Scan-Order Optimisation: A Bilevel Proxy--FEA Diagnostic Framework for Reward and World-Model Diagnosis

arXiv:2605.25063v1 Announce Type: new Abstract: Reinforcement learning offers a promising approach for scan-order optimisation in laser additive manufacturing, where sequential scan decisions critical

RepetitionCurse: Measuring and Understanding Router Imbalance in Mixture-of-Experts LLMs under DoS Stress

arXiv:2512.23995v2 Announce Type: replace-cross Abstract: Mixture-of-Experts architectures have become the standard for scaling large language models due to their superior parameter efficiency. To acc

RePlan-Bot: Multi-Level Replanning for Embodied Instruction Following

arXiv:2605.25851v1 Announce Type: new Abstract: Embodied instruction following (EIF) requires agents to understand and execute complex natural language commands within interactive 3D environments. Des

Representation Without Control: Testing the Realization Effect in Language Models

arXiv:2605.25151v1 Announce Type: new Abstract: Large language models are increasingly used as behavioral simulators, but it remains unclear when their outputs reflect human-like cognitive mechanisms

RepSAM: Bridging Foundation Models to Robotic Vision via Representation-Guided Adaptation

arXiv:2605.25495v1 Announce Type: new Abstract: Robotic perception in unstructured environments remains challenging despite the zero-shot capabilities of foundation models such as SAM. This work attri

Residual Drift Dominates Contradiction in Multi-Turn Constraint Reasoning

arXiv:2605.23940v1 Announce Type: new Abstract: How do multi-turn reasoning systems fail? The expected answer is logical contradiction, in which the system's maintained state becomes unsatisfiable. We

Rethinking Continual Anomaly Detection on the Edge: Benchmarking Under Realistic Industrial Conditions

arXiv:2605.24251v1 Announce Type: new Abstract: Continual anomaly detection (CAD) addresses the need for industrial inspection systems to adapt to evolving production conditions, yet existing methods

Rethinking Weak Supervision in Anomaly Detection: A Comprehensive Benchmark

arXiv:2605.26068v1 Announce Type: cross Abstract: Weakly supervised anomaly detection (WSAD) has developed in three primary directions: incomplete, inexact, and inaccurate supervision. However, these

Retrying vs Resampling in AI Control

arXiv:2605.26047v1 Announce Type: new Abstract: AI coding scaffolds like Claude Code and Codex use extit{retrying}: blocking actions flagged as risky and continuing the trajectory. We study retrying f

Reward-free Alignment for Conflicting Objectives

arXiv:2602.02495v3 Announce Type: replace-cross Abstract: Direct alignment methods are increasingly used to align large language models (LLMs) with human preferences. However, many real-world alignmen

Riemannian-Manifold Steering: Geometry-Aware Generative Autoencoders for Label-Free Steering

arXiv:2605.24942v1 Announce Type: cross Abstract: Steering a language model - intervening on its internal activations to change downstream behaviour - has recently expanded beyond linear interpolation

RL with Learnable Textual Feedback: A Bilevel Approach

arXiv:2605.24547v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards can improve LLM reasoning, but learning remains sample-inefficient when terminal rewards are sparse. This

RoboManipBaselines: A Unified Framework for Imitation Learning in Robotic Manipulation across Real and Simulation Environments

arXiv:2509.17057v3 Announce Type: replace Abstract: We present RoboManipBaselines, an open-source software framework for imitation learning research in robotic manipulation. The framework supports the

Robust Fuzzy Multi-view Learning under View Conflict

arXiv:2605.24475v1 Announce Type: cross Abstract: Trusted multi-view classification aims to deliver reliable fusion for accurate predictions and has recently attracted substantial attention in both ac

RotMoLE: Enhancing Mixture of Low-Rank Experts through Rotational Gating Mechanism

model-releasesarxiv-cs-cl

arXiv:2605.25565v1 Announce Type: cross Abstract: While Large Language Models (LLMs) are commonly fine-tuned to handle domain-specific tasks before being applied to vertical applications, adapting the

SafeCtrl-RL: Inference-Time Adaptive Behaviour Control for LLM Dialogue via RL-Driven Prompt Optimisation

arXiv:2605.25984v1 Announce Type: cross Abstract: Ensuring safe and contextually appropriate behaviour in Large Language Models (LLMs) remains a critical challenge for real-world deployment. We presen

Safety Generalization Under Distribution Shift in Safe Reinforcement Learning: A Diabetes Testbed

arXiv:2601.21094v2 Announce Type: replace-cross Abstract: Safe Reinforcement Learning (RL) algorithms are typically evaluated under fixed training conditions. We investigate whether training-time safe

SafetyRepro: Configuration-Conditional Rank Instability on Alignment Benchmarks

arXiv:2605.25492v1 Announce Type: new Abstract: Pairwise model comparisons drawn from foundation-model benchmarks ('A is safer than B') are read as quantitative verdicts but hinge on harness choices b

ScaleAcross Explorer: Exploring Communication Optimization for Scale-Across AI Model Training

arXiv:2605.24326v1 Announce Type: cross Abstract: The rapid scaling of large language model training requires distributing GPU resources across multiple data center buildings and regions. We refer to

Schema-Grounded LLM Extraction for FHIR Patient Digital Twins

model-releasesarxiv-cs-cl

arXiv:2601.05847v2 Announce Type: replace Abstract: We revisit the problem of constructing interoperable patient digital twins from unstructured electronic health records (EHRs) and argue that the tas

Second Guess: Detecting Uncertainty Through Abstention and Answer Stability in Small Language Models

arXiv:2605.25394v1 Announce Type: new Abstract: Large language models often generate confident but incorrect answers rather than abstaining when uncertain. This problem is particularly acute for small

Security in the Fine-Tuning Lifecycle of Large Language Models: Threats, Defenses,Evaluation, and Future Directions

arXiv:2605.25073v1 Announce Type: cross Abstract: Background: Fine-tuning is central to adapting pre-trained Large Language Models (LLMs) to downstream tasks, but its reliance on training data, parame

SemanticZip: A Pilot Framework for Lossy Text Compression with LLMs as Semantic Decompressors

arXiv:2605.24541v1 Announce Type: cross Abstract: Text compression for large language model (LLM) systems is usually framed as token deletion, retrieval, summarization, or exact reconstruction. We stu

'Si'multaneous 'S'patial-'T'emporal Message Passing for Dynamic Graph Representation Learning

arXiv:2605.25548v1 Announce Type: cross Abstract: Dynamic graph neural networks (DGNNs) that operate on snapshot sequences typically fall into one of two categories. Temporal-first approaches build pe

SimuWoB: Simulating Real-World Mobile Apps for Fast and Faithful GUI Agent Benchmarking

arXiv:2605.25160v1 Announce Type: new Abstract: Mobile GUI agents powered by large language models have progressed rapidly, creating urgent needs for realistic and comprehensive evaluation. Existing b

SkillEvolBench: Benchmarking the Evolution from Episodic Experience to Procedural Skills

arXiv:2605.24117v1 Announce Type: new Abstract: Large language model (LLM) agents accumulate rich episodic trajectories while solving real-world tasks, but it remains unclear whether such experience c

SLAP: Stratified Loss-based Pruning for On-Policy Data-Efficient Instruction Tuning

model-releasesarxiv-cs-cl

arXiv:2605.23969v1 Announce Type: new Abstract: Instruction tuning has optimized the specialized capabilities of large language models (LLMs), but it often requires extensive datasets and prolonged tr

Small Models, Strong Priors: Architectural Inductive Bias for Parameter-Efficient Neural PDE Solvers

arXiv:2605.25949v1 Announce Type: cross Abstract: Neural PDE solvers have followed the scaling trajectory of vision and language, with recent foundation models reaching billions of parameters. We argu

Smart Timing for Mining: A Deep Learning Framework for Bitcoin Hardware ROI Prediction

arXiv:2512.05402v2 Announce Type: replace-cross Abstract: Bitcoin mining hardware acquisition requires strategic timing due to volatile markets, rapid technological obsolescence, and protocol-driven r

SMDD-Bench: Can LLMs Solve Real-World Small Molecule Drug Design Tasks?

arXiv:2605.21740v2 Announce Type: replace Abstract: LLM agents have incredible potential for scientific discovery applications. However, the performance of LLM agents on real-world, small molecule dru

SODE: Analyzing Social Dynamics in LLM Agents

arXiv:2605.23949v1 Announce Type: cross Abstract: As Large Language Models (LLMs) evolve into interactive agents, understanding their behavioral alignment within human social dynamics becomes essentia

SoK: A Comprehensive Security Analysis of Jailbreak Resilience in GPT and DeepSeek Models

arXiv:2506.18543v2 Announce Type: replace-cross Abstract: The rapid proliferation of Large Language Models (LLMs) has heightened concerns regarding their exposure to jailbreak attacks, which craft adv

SomaliBench Eval: Measuring English-to-Somali Refusal Gaps in Open-Weight Language Models

arXiv:2605.25420v1 Announce Type: cross Abstract: Large language model safety evaluation remains heavily English-centered, leaving low-resource languages under-measured even when models are deployed g

Some ideas for what comes next, May 2026

model-releasesinterconnects

This article from Interconnects explores speculative ideas and predictions about technological developments and trends expected around May 2026, likely covering emerging AI capabilities, infrastructur

Sources: Chinese government agencies begin imposing overseas travel restrictions on individuals involved in advanced AI work, including at Alibaba and DeepSeek (Bloomberg)

Bloomberg: Sources: Chinese government agencies begin imposing overseas travel restrictions on individuals involved in advanced AI work, including at Alibaba and DeepSeek — China is restricting overse

model-releasestechmeme

Spectral Probe-Circuits: A Three-Step Recipe for Identifying Attention-Head Circuits in Pretrained Transformers

arXiv:2605.24059v1 Announce Type: cross Abstract: We present a three-step recipe for identifying attention-head circuits in pretrained transformers. A per-head spectral signal -- the time-integrated p

Spectral Retrieval: Multi-Scale Sinc Convolution over Token Embeddings for Localized Retrieval in LLM Multi-Agent Systems

arXiv:2605.24764v1 Announce Type: cross Abstract: [Abridged] - Spectral Retrieval is a plug-in re-ranking stage that interpolates between per-token MaxSim and mean-pool retrieval through a multi-scale

Split-Merge: A Difference-based Approach for Dominant Eigenvalue Problem

arXiv:2501.15131v3 Announce Type: replace-cross Abstract: The computation of the dominant eigenpair for symmetric positive semidefinite matrices is fundamental in numerical optimization. This work shi

Spotify launches a library of over 650 narrated long-form magazine articles in English for Premium users; free users can buy articles 'individually for $1.99' (Jess Weatherbed/The Verge)

Jess Weatherbed / The Verge: Spotify launches a library of over 650 narrated long-form magazine articles in English for Premium users; free users can buy articles “individually for $1.99” — More than

model-releasestechmeme

Stein Variational Ergodic Surface Coverage with SE(3) Constraints

arXiv:2603.09458v3 Announce Type: replace Abstract: Surface manipulation tasks require robots to generate trajectories that comprehensively cover complex 3D surfaces while maintaining precise end-effe