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Reinforcement Learning with LLM-Guided Action Spaces for Synthesizable Lead Optimization

arXiv:2604.07669v2 Announce Type: replace Abstract: Lead optimization in drug discovery requires improving therapeutic properties while ensuring that molecular modifications correspond to feasible syn

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Reinforcement Learning with Markov Risk Measures and Multipattern Risk Approximation

DGX agent

arXiv:2605.00654v1 Announce Type: new Abstract: For a risk-averse finite-horizon Markov Decision Problem, we introduce a special class of Markov coherent risk measures, called mini-batch measures. We

safetyarxiv-cs-lg

4 May 2026

ReLay: Personalized LLM-Generated Plain-Language Summaries for Better Understanding, but at What Cost?

arXiv:2605.00468v1 Announce Type: new Abstract: Plain Language Summaries (PLS) aim to make research accessible to lay readers, but they are typically written in a one-size-fits-all style that ignores

safetyarxiv-cs-cl

Remote SAMsing: From Segment Anything to Segment Everything

model-releasesarxiv-cs-cv

arXiv:2605.00256v1 Announce Type: new Abstract: SAM2 produces high-quality zero-shot segmentation on natural images, but applying it to large remote sensing scenes exposes two problems: (1) its mask g

Representation in large language models

arXiv:2501.00885v2 Announce Type: replace Abstract: The extraordinary success of recent Large Language Models (LLMs) on a diverse array of tasks has led to an explosion of scientific and philosophical

ResRL: Boosting LLM Reasoning via Negative Sample Projection Residual Reinforcement Learning

arXiv:2605.00380v1 Announce Type: cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) enhances reasoning of Large Language Models (LLMs) but usually exhibits limited generation diver

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Resting Neurons, Active Insights: Robustify Activation Sparsity for Large Language Models

arXiv:2512.12744v3 Announce Type: replace Abstract: Activation sparsity offers a compelling route to accelerate large language model (LLM) inference by selectively suppressing hidden activations, yet

Rethinking LLM Ensembling from the Perspective of Mixture Models

arXiv:2605.00419v1 Announce Type: cross Abstract: Model ensembling is a well-established technique for improving the performance of machine learning models. Conventionally, this involves averaging the

RETO: A Rotary-Enhanced Transformer Operator for High-Fidelity Prediction of Automotive Aerodynamics

arXiv:2605.00062v1 Announce Type: cross Abstract: Rapid aerodynamic evaluation is crucial for modern vehicle design, yet existing neural operators struggle to capture intricate spatial correlations. W

Retrieval-Augmented Reasoning for Chartered Accountancy

model-releasesarxiv-cs-cl

arXiv:2605.00257v1 Announce Type: new Abstract: The inception of Large Language Models (LLMs) has catalyzed AI adoption in the finance sector, yet their reliability in complex, jurisdiction-specific t

Revealing graph bandits for maximizing local influence

arXiv:2605.00489v1 Announce Type: new Abstract: We study a graph bandit setting where the objective of the learner is to detect the most influential node of a graph by requesting as little information

Reward Modeling from Natural Language Human Feedback

arXiv:2601.07349v3 Announce Type: replace Abstract: Reinforcement Learning with Verifiable reward (RLVR) on preference data has become the mainstream approach for training Generative Reward Models (GR

Riemannian MeanFlow

arXiv:2602.07744v3 Announce Type: replace Abstract: Diffusion and flow models have become the dominant paradigm for generative modeling on Riemannian manifolds, with successful applications in protein

Rivers of Blood

Rivers of Blood This parasitic idea stems from the anthropologists of peace who preached the Noble Savage canard (as per Jean-Jacques Rousseau). @elonmusk is exactly right. History is paved with river

industryelon-musk--x

Applications

Robust Fusion of Object-Level V2X for Learned 3D Object Detection

arXiv:2605.00595v1 Announce Type: new Abstract: Perception for automated driving is largely based on onboard environmental sensors, such as cameras and radar, which are cost-effective but limited by l

applicationsarxiv-cs-cv

ROSA: Robust and Energy-Efficient Microring-Based Optical Neural Networks via Optical Shift-and-Add and Layer-Wise Hybrid Mapping

arXiv:2605.00032v1 Announce Type: cross Abstract: This work presents ROSA, a microring-based optical neural network architecture that improves robustness and energy efficiency using an optical shift-a

RouteProfile: Elucidating the Design Space of LLM Profiles for Routing

arXiv:2605.00180v1 Announce Type: cross Abstract: As the large language model (LLM) ecosystem expands, individual models exhibit varying capabilities across queries, benchmarks, and domains, motivatin

RSAT: Structured Attribution Makes Small Language Models Faithful Table Reasoners

model-releasesarxiv-cs-cl

arXiv:2605.00199v1 Announce Type: new Abstract: When a language model answers a table question, users have no way to verify which cells informed which reasoning steps. We introduce RSAT, a method that

Applications

RT @Box: We’re excited to be part of the @pinecone Nexus launch! For AI agents to actually work in the enterprise, they need context from…

Box announced its participation in Pinecone's Nexus launch, emphasizing that enterprise AI agents require contextual access to organizational data and content. The partnership highlights the integrati

applicationspinecone--x

Tools

RT @LangChain: Excited to partner with @pinecone!

LangChain announced a partnership with Pinecone, a vector database platform, to integrate vector search capabilities with LangChain's framework for building applications with large language models. Th

toolspinecone--x

RTPrune: Reading-Twice Inspired Token Pruning for Efficient DeepSeek-OCR Inference

model-releasesarxiv-cs-cv

arXiv:2605.00392v1 Announce Type: new Abstract: DeepSeek-OCR leverages visual-text compression to reduce long-text processing costs and accelerate inference, yet visual tokens remain prone to redundan

Agents

RunAgent: Interpreting Natural-Language Plans with Constraint-Guided Execution

arXiv:2605.00798v1 Announce Type: cross Abstract: Humans solve problems by executing targeted plans, yet large language models (LLMs) remain unreliable for structured workflow execution. We propose Ru

agentsarxiv-cs-cl

SAGA: Workflow-Atomic Scheduling for AI Agent Inference on GPU Clusters

arXiv:2605.00528v1 Announce Type: cross Abstract: AI agents execute tens to hundreds of chained LLM calls per task, yet GPU schedulers treat each call as independent, discarding gigabytes of intermedi

SAP acquires Dremio, Prior Labs to enhance its tabular AI capabilities

SAP SE today announced plans to acquire two startups that help organizations analyze tabular data, or information stored in rows and columns. Santa Clara, California-based Dremio Inc. raised more than

industrysiliconangle

SAP to acquire Dremio, an open data lakehouse provider, and Prior Labs, which it pledges to invest €1B in over four years, hoping to create a frontier AI lab (Larry Dignan/Constellation Research)

Larry Dignan / Constellation Research: SAP to acquire Dremio, an open data lakehouse provider, and Prior Labs, which it pledges to invest €1B in over four years, hoping to create a frontier AI lab — S

industrytechmeme

SAVGO: Learning State-Action Value Geometry with Cosine Similarity for Continuous Control

arXiv:2605.00787v1 Announce Type: new Abstract: While representation and similarity learning have improved the sample efficiency of Reinforcement Learning (RL), they are rarely used to shape policy up

SC-Taxo: Hierarchical Taxonomy Generation under Semantic Consistency Constraints using Large Language Models

model-releasesarxiv-cs-cl

arXiv:2605.00620v1 Announce Type: new Abstract: Scientific literature is expanding at an unprecedented pace, making it increasingly challenging to efficiently organize and access domain knowledge. A h

Scalable Context-Aware Graph Attention for Unsupervised Anomaly Detection in Large-Scale Mobile Networks

arXiv:2605.00482v1 Announce Type: new Abstract: Mobile network operators must monitor thousands of heterogeneous network elements across the radio access network and the packet core, each exposing hig

Scalable Learning in Structured Recurrent Spiking Neural Networks without Backpropagation

arXiv:2605.00402v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs) provide a promising framework for energy-efficient and biologically grounded computation; however, scalable learning in

Scale-Aware Adversarial Analysis: A Diagnostic for Generative AI in Multiscale Complex Systems

arXiv:2605.00510v1 Announce Type: cross Abstract: Complex physical systems, from supersonic turbulence to the macroscopic structure of the universe, are governed by continuous multiscale dynamics. Whi

researcharxiv-cs-cv

Scaling data and AI with Managed Service for Apache Airflow

model-releasesgoogle-cloud-ai

Orchestration is no longer just about moving data; it is about governing enterprise intelligence. To reflect our deep commitment to and embrace of open-source software, we shared earlier that Cloud Co

Applications

Scaling Federated Linear Contextual Bandits via Sketching

arXiv:2605.00500v1 Announce Type: new Abstract: In federated contextual linear bandits, high data dimensionality incurs prohibitive computation and communication costs: local agents perform O(d^3)-tim

applicationsarxiv-cs-lg

Scaling Reasoning Hop Exposes Weaknesses: Demystifying and Improving Hop Generalization in Large Language Models

arXiv:2601.21214v2 Announce Type: replace Abstract: Chain-of-thought (CoT) reasoning has become the standard paradigm for enabling Large Language Models (LLMs) to solve complex problems. However, rece

Scaling Video Understanding via Compact Latent Multi-Agent Collaboration

arXiv:2605.00444v1 Announce Type: new Abstract: Multi-modal large language models (MLLMs) advance vision language understanding but face inherent limitations in long-video tasks due to bounded percept

safetyarxiv-cs-cv

SCAN: Structured Capability Assessment and Navigation for LLMs

arXiv:2505.06698v4 Announce Type: replace Abstract: Evaluating Large Language Models (LLMs) has become increasingly important, with automatic evaluation benchmarks gaining prominence as alternatives t

Score-based Greedy Search for Structure Identification of Partially Observed Linear Causal Models

arXiv:2510.04378v2 Announce Type: replace Abstract: Identifying the structure of a partially observed causal system is essential to various scientific fields. Recent advances have focused on constrain

ScreenParse: Moving Beyond Sparse Grounding with Complete Screen Parsing Supervision

model-releasesarxiv-cs-cv

arXiv:2602.14276v2 Announce Type: replace Abstract: Modern computer-use agents (CUA) must perceive a screen as a structured state, what elements are visible, where they are, and what text they contain

Tools

see the talk version, out now thanks to @steveruizok https://x.com/aiDotEngineer/status/2050243598676013312

see the talk version, out now thanks to @steveruizok https://x.com/aiDotEngineer/status/2050243598676013312 What if chat is the wrong interface for managing agents? In this talk, @steveruizok shows wh

toolsswyx--x

Selfie-Capture Dynamics as an Auxiliary Signal Against Deepfakes and Injection Attacks for Mobile Identity Verification

arXiv:2605.00218v1 Announce Type: cross Abstract: Mobile remote identity verification (RIdV) systems are exposed to attacks that manipulate or replace the facial video stream, including presentation a

Semantic Level of Detail for Knowledge Graphs: Discovering Abstraction Boundaries via Spectral Heat Diffusion

arXiv:2603.08965v2 Announce Type: replace Abstract: Graph-structured knowledge systems -- from knowledge graphs to GraphRAG pipelines -- organize information into hierarchical communities, yet lack a

Local Ai

Sentinel: an open-source local-first desktop app for AI coding

Sentinel is a local-first AI coding desktop application built with Rust and Tauri that automatically routes coding tasks to appropriate models based on task complexity. Instead of swapping between mul

local-air-ollama

SHIFT: Robust Double Machine Learning for Average Dose-Response Functions under Heavy-Tailed Contamination

arXiv:2605.00176v1 Announce Type: cross Abstract: Double-machine-learning pipelines for the Average Dose-Response Function rely on kernel-weighted local-linear smoothers, which inherit unbounded funct

shipped Promptloop 🌀 Claude Code but for your prompts. a CLI agent that runs the full prompt-eval loop in one chat session: create test cas…

model-releasesharrison-chase--x

shipped Promptloop 🌀 Claude Code but for your prompts. a CLI agent that runs the full prompt-eval loop in one chat session: create test cases → run across models → generate reports → propose prompt →

Short Chains, Deep Thoughts: Balancing Reasoning Efficiency and Intra-Segment Capability via Split-Merge Optimization

arXiv:2602.03141v3 Announce Type: replace Abstract: While Large Reasoning Models (LRMs) have demonstrated impressive capabilities in solving complex tasks through the generation of long reasoning chai

SIMON: Saliency-aware Integrative Multi-view Object-centric Neural Decoding

arXiv:2605.00401v1 Announce Type: new Abstract: Recent EEG-to-image retrieval methods leverage pretrained vision encoders and foveation-inspired priors, but typically assume a fixed, center-focused vi

safetyarxiv-cs-cv

Agents

since babyagi, i've seen hundreds of agentic products and pitches there are only a few i immediately loved, and only one that i invested in …

since babyagi, i've seen hundreds of agentic products and pitches there are only a few i immediately loved, and only one that i invested in past my usual entry stage that was cofounder 1 from @intelli

agentsyohei-nakajima--x

Singapore Airlines has just announced that it is adopting SpaceX's @Starlink. The rollout will begin in Q1 2027 and be completed by end of 2…

Singapore Airlines has just announced that it is adopting SpaceX's @Starlink. The rollout will begin in Q1 2027 and be completed by end of 2029. 'With more than 10,000 satellites launched to low Earth

industryelon-musk--x

SketchGuard: Scaling Byzantine-Robust Decentralized Federated Learning via Sketch-Based Screening

arXiv:2510.07922v4 Announce Type: replace Abstract: Decentralized Federated Learning (DFL) enables privacy-preserving collaborative training without centralized servers but remains vulnerable to Byzan