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Scaling Small Agents Through Strategy Auctions

arXiv:2602.02751v2 Announce Type: replace-cross Abstract: Small language models are increasingly viewed as a promising, cost-effective approach to agentic AI, with proponents claiming they are suffici

agentsarxiv-cs-ai

SCDBench: A Benchmark for LLM-Based Smart Contract Decompilers

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arXiv:2605.29059v1 Announce Type: cross Abstract: Smart contract decompilation aims to recover high-level source code from bytecode, but evaluating decompilers remains difficult because existing studi

model-releasesarxiv-cs-ai

29 May 2026

Hardware

ScheduleStream: Temporal Planning with Samplers for GPU-Accelerated Multi-Arm Task and Motion Planning & Scheduling

arXiv:2511.04758v2 Announce Type: replace-cross Abstract: Bimanual and humanoid robots are appealing because of their human-like ability to leverage multiple arms to efficiently complete tasks. Howeve

hardwarearxiv-cs-ai

SchGen: PCB Schematic Generation with Semantic-Grounded Code Representations

arXiv:2605.30345v1 Announce Type: new Abstract: Printed circuit board (PCB) schematic design defines nearly all electronic hardware, but it remains manual and expertise-intensive. While generative AI

agentsarxiv-cs-ai

SciIntBench: Measuring LLM Compliance with Research Integrity Norms Under Adversarial Framing

arXiv:2605.29468v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to support scientific work, but it is unclear whether they uphold responsible conduct of research (

SCoOP: Semantic Consistent Opinion Pooling for Uncertainty Quantification in Multiple Vision-Language Model Systems

arXiv:2603.23853v3 Announce Type: replace Abstract: Combining multiple Vision-Language Models (VLMs) can enhance multimodal reasoning and robustness, but aggregating heterogeneous models' outputs ampl

SCOPE: A Lightweight-training LLM Framework for Air Traffic Control Readback Monitoring

arXiv:2605.29543v1 Announce Type: cross Abstract: Pilot readback of Air Traffic Control (ATC) voice instructions is a primary safeguard against miscommunication in air transportation. However, readbac

SCOPE: Prompt Evolution for Enhancing Agent Effectiveness

arXiv:2512.15374v2 Announce Type: replace Abstract: Large Language Model (LLM) agents are increasingly deployed in environments that generate massive, dynamic contexts. However, a critical bottleneck

SDF-Net: Structure-Aware Disentangled Feature Learning for Opticall-SAR Ship Re-identification

model-releasesarxiv-cs-cv

arXiv:2603.12588v2 Announce Type: replace Abstract: Cross-modal ship re-identification (ReID) between optical and synthetic aperture radar (SAR) imagery is fundamentally challenged by the severe radio

SEAL: Can Saturated Benchmarks Be Revived by LLM-as-a-Meta-Judge?

arXiv:2605.30104v1 Announce Type: new Abstract: Widely used language-model benchmarks are increasingly saturated, with frontier systems often receiving near-tied scores that standard metrics cannot re

agentsarxiv-cs-cl

Securing SIM-Assisted Wireless Networks via Quantum Reinforcement Learning

arXiv:2602.13238v2 Announce Type: replace-cross Abstract: Stacked intelligent metasurfaces (SIMs) have recently emerged as a powerful wave-domain technology that enables multi-stage manipulation of el

safetyarxiv-cs-lg

Tutorials

Seeing through boxes: Non-Line-of-Sight 3D Reconstruction from Radar Signals

arXiv:2605.29098v1 Announce Type: new Abstract: Reconstructing object geometry from radio frequency (RF) signals is fundamentally challenging due to the lensless imaging nature of RF sensing, which le

tutorialsarxiv-cs-cv

Selecting Hyperparameters for Tree-Boosting

arXiv:2602.05786v2 Announce Type: replace Abstract: Tree-boosting is a widely used machine learning technique for tabular data. However, its out-of-sample accuracy is critically dependent on multiple

Selection Hyper-heuristics Can Automatically Adjust the Learning Period to Optimally Solve Pseudo-Boolean Problems

arXiv:2605.29916v1 Announce Type: cross Abstract: The Random Gradient hyper-heuristic was recently shown to be able to learn the optimal neighbourhood size when optimizing the LeadingOnes benchmark vi

Selective QA over Conflicting Multi-Source Personal Memory: A Diagnostic Testbed and Method Comparison

arXiv:2605.30087v1 Announce Type: new Abstract: Emerging personal AI agents are moving toward persistent, multi-source memory. This creates an evaluation problem: systems must decide how to use confli

self-modification

Self-modification in AI systems refers to the capability of an artificial intelligence to alter its own code, parameters, or behavior patterns without external intervention. This concept, discussed by

agentsyohei-nakajima--x

Self-Play Reinforcement Learning under Imperfect Information in Big 2

arXiv:2605.28863v1 Announce Type: cross Abstract: Imperfect-information multiplayer games test whether agents can act under hidden information, sparse rewards, and non-stationary opponents. We study t

safetyarxiv-cs-ai

Self-Trained Verification for Training- and Test-Time Self-Improvement

arXiv:2605.30290v1 Announce Type: cross Abstract: Self-improvement at scale has been a longstanding goal for reasoning models, and there are two natural places to do it: at test time, through verifica

Semantic and Visual Evidence for Efficient Long-Video Reasoning: A Solution for the HD-EPIC VQA Challenge

arXiv:2605.29402v1 Announce Type: cross Abstract: Understanding long-form egocentric videos remains challenging for multimodal large language models (MLLMs) due to limited context length and insuffici

Industry

SentinelOne's stock closes down 8% after the company announced plans to lay off 8% of its workforce and forecasted Q2 and FY revenue guidance below estimates (Samantha Subin/CNBC)

Samantha Subin / CNBC: SentinelOne's stock closes down 8% after the company announced plans to lay off 8% of its workforce and forecasted Q2 and FY revenue guidance below estimates — SentinelOne share

industrytechmeme

Sequential Physics-Constrained Neural Operator Forward Modeling for the extit{Norne} Reservoir System

model-releasesarxiv-cs-lg

arXiv:2605.28909v1 Announce Type: new Abstract: We develop a comprehensive mathematical and computational framework for sequential surrogate modeling of three-phase black-oil reservoir dynamics using

SERC: LDPC-Inspired Semantic Error Correction for Retrieval-Augmented Generation

arXiv:2605.28837v1 Announce Type: cross Abstract: While Large Language Models (LLMs) have demonstrated remarkable capabilities, their reliability is significantly compromised by hallucinations. Existi

Applications

Server-Proximal Aggregation for Federated Domain-Incremental Learning under Partial Participation: Task-Uniform Convergence and Backward Transfer

arXiv:2601.22274v2 Announce Type: replace Abstract: Real-world federated systems seldom operate on static data: input distributions drift while privacy rules forbid raw-data sharing. We study this set

applicationsarxiv-cs-lg

SGMD: Score Gradient Matching Distillation for Few-Step Video Diffusion Distillation

arXiv:2605.30116v1 Announce Type: new Abstract: Distribution Matching Distillation (DMD) is a widely used paradigm for accelerating inference in few-step video diffusion models. However, DMD-style vid

safetyarxiv-cs-cv

Shame on you Apple, sending @mcuban’s thoughtful email to spam. Seriously? Glad I have learned not to trust your algorithm.

Gary Marcus criticizes Apple's email filtering system for incorrectly routing Mark Cuban's message to spam, highlighting a failure in Apple's spam detection algorithm. The post reflects concerns about

safetygary-marcus--x

ShapleyLaw: A Game-Theoretic Approach to Multilingual Scaling Laws

arXiv:2603.17945v2 Announce Type: replace Abstract: In multilingual pretraining, the test loss of a pretrained model is heavily influenced by the proportion of each language in the pretraining data, n

researcharxiv-cs-cl

SigmaMedStat: Temporal Signal Modeling for ICU False Alarm Reduction

arXiv:2605.29236v1 Announce Type: new Abstract: Alarm fatigue in intensive care units (ICUs) is a well documented patient safety crisis. Clinical monitors generate 350 or more alarms per patient per d

safetyarxiv-cs-lg

Simulation-based planning of Motion Sequences for Automated Procedure Optimization in Multi-Robot Assembly Cells

arXiv:2507.23270v2 Announce Type: replace Abstract: Reconfigurable multi-robot cells offer a promising approach to meet fluctuating assembly demands. However, the recurrent planning of their configura

researcharxiv-cs-ro

Singularity-aware Optimization via Randomized Geometric Probing: Towards Stable Non-smooth Optimization

arXiv:2605.29547v1 Announce Type: cross Abstract: Deep learning optimization relies heavily on the assumption of smooth loss landscapes, a condition systematically violated by modern architectures due

Singularity-free dynamical invariants-based quantum control

arXiv:2510.15340v2 Announce Type: replace-cross Abstract: State preparation is a cornerstone of quantum technologies, underpinning applications in computation, communication, and sensing. Its importan

Applications

Size Transferability of Graph Transformers with Convolutional Positional Encodings

arXiv:2602.15239v2 Announce Type: replace Abstract: Transformers have achieved remarkable success across domains, motivating the rise of Graph Transformers (GTs) as attention-based architectures for g

applicationsarxiv-cs-lg

Skill-Pro: Learning Reusable Skills from Experience via Non-Parametric PPO for LLM Agents

arXiv:2602.01869v3 Announce Type: replace Abstract: LLM-driven agents excel at sequential decision-making but often rely on on-the-fly reasoning, re-deriving solutions even in recurring scenarios. Thi

SkillBrew: Multi-Objective Curation of Skill Banks for LLM Agents

arXiv:2605.29440v1 Announce Type: cross Abstract: Retrieval-augmented LLM agents increasingly rely on curated skill banks: collections of reusable textual principles that guide decision making on comp

agentsarxiv-cs-ai

SkillsInjector: Dynamic Skill Context Construction for LLM Agents

arXiv:2605.29794v1 Announce Type: new Abstract: LLM agents now draw on growing skill libraries to handle complex tasks. However, injecting more skills does not always improve task completion and can e

SLAD : Shared LoRA Adapters for Task Specific Distillation

model-releasesarxiv-cs-cv

arXiv:2605.29726v1 Announce Type: new Abstract: In the context of resource-constrained environments such as embedded systems, adapting reduced-size foundation models to downstream tasks has become inc

Slogans or Stance? A Label-Light Diagnostic for Entrepreneurial-Discourse Measurement on Chinese SOE Speeches

arXiv:2605.29188v1 Announce Type: new Abstract: Dictionary methods, topic models, and embedding-similarity scorers are widely used in CSS and management research to measure constructs such as 'entrepr

researcharxiv-cs-cl

SM2ITH: Safe Mobile Manipulation with Interactive Human Prediction via Task-Hierarchical Bilevel Model Predictive Control

arXiv:2511.17798v2 Announce Type: replace Abstract: Mobile manipulators are designed to perform complex sequences of navigation and manipulation tasks in human-centered environments. While recent opti

researcharxiv-cs-ro

Small Agent Group is the Future of Digital Health

arXiv:2602.08013v2 Announce Type: replace Abstract: The rapid adoption of large language models (LLMs) in digital health has been driven by a 'scaling-first' philosophy, i.e., the assumption that clin

SMolLM: Small Language Models Learn Small Molecular Grammar

model-releasesarxiv-cs-lg

arXiv:2605.06322v2 Announce Type: replace Abstract: Language models for molecular design have scaled to hundreds of millions of parameters, yet how they learn chemical grammar is poorly understood. We

Soften the Mask: Adaptive Temporal Soft Mask for Efficient Dynamic Facial Expression Recognition

arXiv:2502.21004v2 Announce Type: replace Abstract: Dynamic Facial Expression Recognition (DFER) facilitates the understanding of psychological intentions through non-verbal communication. Existing me

researcharxiv-cs-cv

Solved in Unit Domain: JacobiNet for Differentiable Coordinate-Transformed PINNs

arXiv:2508.02537v3 Announce Type: replace Abstract: Physics-Informed Neural Networks (PINNs) offer a powerful framework for solving PDEs by embedding physical laws into the learning process. However,

Solving Integer Linear Programming with Parallel Tempering

arXiv:2605.29366v1 Announce Type: new Abstract: Integer Linear Programming (ILP) serves as a versatile framework for modeling a wide range of combinatorial optimization problems, typically addressed b

Solving the Offline and Online Min-Max Problem of Non-smooth Submodular-Concave Functions: A Zeroth-Order Approach

arXiv:2601.21243v2 Announce Type: replace-cross Abstract: We consider max-min and min-max problems with objective functions that are possibly non-smooth, submodular with respect to the minimiser and c

Some fun Gemini Omni use cases from the community 🧵👇

model-releasesgoogle-ai--x

This X thread from Google AI showcases community-created use cases and applications of Gemini Omni, Google's multimodal AI model. The post likely highlights practical and creative examples of how user

SoundnessBench: Can Your AI Scientist Really Tell Good Research Ideas from Bad Ones?

model-releasesarxiv-cs-lg

arXiv:2605.30329v1 Announce Type: new Abstract: Autonomous AI research agents aim to accelerate scientific discovery by automating the research pipeline, from hypothesis generation to peer review. How

Source-Grounded Semantic Reinforcement Learning for Low-Resource Target-Language Generation

arXiv:2605.29502v1 Announce Type: cross Abstract: Low-resource target-language generation is often limited by scarce parallel data, while high-resource source-language monolingual data is abundant but

Hardware

Sources: ByteDance has partnered with chipmaker InnoStar to develop an AI inference chip modeled after Groq's LPUs, which are built to run AI models at low cost (The Information)

The Information: Sources: ByteDance has partnered with chipmaker InnoStar to develop an AI inference chip modeled after Groq's LPUs, which are built to run AI models at low cost — TikTok owner ByteDan

hardwaretechmeme

Sources: Microsoft is working on an app that will include GitHub Copilot, Copilot chat, Copilot Cowork, and a new agentic workflow tool called Autopilot (Sebastian Herrera/Fortune)

Sebastian Herrera / Fortune: Sources: Microsoft is working on an app that will include GitHub Copilot, Copilot chat, Copilot Cowork, and a new agentic workflow tool called Autopilot — Microsoft needs

agentstechmeme