Search: “models”

Beyond Scalar Objectives: Expert-Feedback-Driven Autonomous Experimentation for Scientific Discovery at the Nanoscale

arXiv:2605.21820v1 Announce Type: new Abstract: Self-driving laboratories or autonomous experimentation are emerging as transformative platforms for accelerating scientific discovery. Bayesian optimiz

agentsarxiv-cs-lg

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Clipping Bottleneck: Stabilizing RLVR via Stochastic Recovery of Near-Boundary Signals

DGX agent

arXiv:2605.22703v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a central paradigm for scaling LLM reasoning, yet its optimization often suffers fr

local-aiarxiv-cs-lg

23 May 2026

Tutorials

ConTact: Contact-First Antibody CDR Design via Explicit Interface Reasoning

arXiv:2605.21600v1 Announce Type: new Abstract: Computational antibody CDR design methods condition on antigen structure to generate binding loops, yet existing architectures conflate two fundamentall

tutorialsarxiv-cs-lg

Corruption-Tolerant Asynchronous Q-Learning with Near-Optimal Rates

arXiv:2509.08933v2 Announce Type: replace Abstract: We study the problem of learning the optimal policy in a discounted, infinite-horizon reinforcement learning (RL) setting in the presence of adversa

Cross-Subject EEG Emotion Recognition Based on Temporal Asynchronous Alignment Contrastive Learning

arXiv:2605.22379v1 Announce Type: cross Abstract: With the advancement of science and technology, the importance of emotion research has become increasingly evident. Electroencephalography (EEG)-based

local-aiarxiv-cs-lg

Discovering Entity-Conditioned Lag Heterogeneity: A Lag-Gated Neural Audit Framework for Panel Time Series

arXiv:2605.21542v1 Announce Type: new Abstract: Country-level temporal panels are widely used in empirical analysis. Researchers often need to audit how different entities respond to historical signal

Embedding-Based Federated Learning with Runtime Governance for Iron Deficiency Prediction

arXiv:2605.21563v1 Announce Type: new Abstract: Recent reviews find that the vast majority of published healthcare federated learning (FL) studies never reach real-world deployment. We developed an em

Evolutionary Multi-Task Optimization for LLM-Guided Program Discovery

arXiv:2605.22613v1 Announce Type: new Abstract: Recent LLM-guided evolutionary search methods have shown that iterative program mutation can discover strong algorithms, but they typically optimize eac

FAME: Failure-Aware Mixture-of-Experts for Message-Level Log Anomaly Detection

arXiv:2605.22779v1 Announce Type: cross Abstract: Production systems generate millions of log lines daily, yet most anomaly detectors operate at the session or window-level, flagging groups of lines r

Healthcare LLM Benchmarks Are Only as Good as Their Explicit Assumptions

arXiv:2605.22612v1 Announce Type: cross Abstract: Benchmarks are necessary for healthcare evaluation, but are not sufficient for predicting deployment performance. Our position is that the evaluation-

Heterogeneous Agent Collaborative Reinforcement Learning

arXiv:2603.02604v2 Announce Type: replace Abstract: We introduce Heterogeneous Agent Collaborative Reinforcement Learning (HACRL), a new Reinforcement Learning from Verifiable Reward (RLVR) problem th

How Many Different Outputs Can a Transformer Generate?

arXiv:2605.22223v1 Announce Type: new Abstract: We study how we can leverage only a handful of characteristics of a transformer's architecture to closely predict the number of different sequences it c

Minimum Description Length based Granular-Ball Tree Regularization for Spectral Clustering

arXiv:2605.22410v1 Announce Type: new Abstract: Spectral clustering largely depends on the affinity graph, yet constructing a graph that preserves reliable local connectivity while adapting to heterog

local-aiarxiv-cs-lg

MOSS: Self-Evolution through Source-Level Rewriting in Autonomous Agent Systems

arXiv:2605.22794v1 Announce Type: cross Abstract: Autonomous agentic systems are largely static after deployment: they do not learn from user interactions, and recurring failures persist until the nex

agentsarxiv-cs-lg

Neural Acceleration for Graph Partitioning

arXiv:2605.21519v1 Announce Type: cross Abstract: Graph Partitioning is a critical problem in numerous scientific and engineering domains including social network analysis, VLSI design, and many more.

Patina @patinaglobal is one of the coolest and most seminal @EarthlingVC portcos Even as a fund that's very focused on immersive computing (…

Patina @patinaglobal is one of the coolest and most seminal @EarthlingVC portcos Even as a fund that's very focused on immersive computing (i.e. physical computing) I've seen very, very few things goi

agentsyohei-nakajima--x

Peekaboo

Peekaboo is likely a technical concept or tool discussed by Jerry Liu, co-founder of LlamaIndex, based on the X platform post. Without access to the specific tweet content, this probably covers an AI

agentsjerry-liu--x

Tutorials

PhylaFlow: Hybrid Flow Matching in Billera-Holmes-Vogtmann Tree Space for Phylogenetic Inference

arXiv:2605.21859v1 Announce Type: cross Abstract: Phylogenetic trees are hybrid objects: branch lengths vary continuously, while topologies change discretely through edge contractions and expansions.

tutorialsarxiv-cs-lg

Plug-in Losses for Evidential Deep Learning: A Simplified Framework for Uncertainty Estimation that Includes the Softmax Classifier

arXiv:2605.22746v1 Announce Type: new Abstract: Real-world sensor-based learning systems require uncertainty estimation that is both reliable and computationally efficient. Evidential Deep Learning (E

Tutorials

Position: The Time for Sampling Is Now! Charting a New Course for Bayesian Deep Learning

arXiv:2605.21765v1 Announce Type: new Abstract: The practical adoption of sampling-based inference (SAI) in Bayesian neural networks (BNNs) remains limited, partly due to persistent misconceptions abo

tutorialsarxiv-cs-lg

Prototype-Guided Classification Sub-Task Decoupling Framework: Enhancing Generalization and Interpretability for Multivariate Time Series

arXiv:2605.22055v1 Announce Type: new Abstract: Time Series Classification (TSC) is a long-standing research problem that has gained increasing attention in recent years with the rapid growth of large

Provable Robustness against Backdoor Attacks via the Primal-Dual Perspective on Differential Privacy

arXiv:2605.21780v1 Announce Type: new Abstract: Randomized smoothing is a powerful tool for certifying robustness to adversarial perturbations, including poisoning attacks via randomized training and

Proxy-Based Approximation of Shapley and Banzhaf Interactions

arXiv:2605.22738v1 Announce Type: new Abstract: Shapley and Banzhaf interactions capture the complex dynamics inherent in modern machine learning applications. However, current estimators for these hi

Q-PhotoNAS: Hybrid Quantum Neural Architecture Search Framework on Photonic Devices

arXiv:2605.22097v1 Announce Type: cross Abstract: Photonic quantum computing is a promising platform for scalable quantum machine learning, but designing effective hybrid architectures remains challen

RADAR: Defending RAG Dynamically against Retrieval Corruption

arXiv:2605.22041v1 Announce Type: cross Abstract: While RAG systems are increasingly deployed in dynamic web search, temporal volatility amplifies their vulnerability to adversarial attacks. Existing

Hardware

Reading Task Failure Off the Activations: A Sparse-Feature Audit of GPT-2 Small on Indirect Object Identification

arXiv:2605.22719v1 Announce Type: new Abstract: We report a small, reproducible audit of which sparse-autoencoder (SAE) features of GPT-2 small fire differently on failed versus successful trials of t

hardwarearxiv-cs-lg

Revisiting Regularized Policy Optimization for Stable and Efficient Reinforcement Learning in Two-Player Games

arXiv:2602.10894v2 Announce Type: replace Abstract: Two-player games such as board games have long been used as traditional benchmarks for reinforcement learning. This work revisits a policy optimizat

Self-orthogonalizing attractor neural networks emerging from the free energy principle

arXiv:2505.22749v2 Announce Type: replace-cross Abstract: Attractor dynamics are a hallmark of many complex systems, including the brain. Understanding how such self-organizing dynamics emerge from fi

TBP-mHC: full expressivity for manifold-constrained hyper connections through transportation polytopes

arXiv:2605.21724v1 Announce Type: new Abstract: Hyper-Connections (HC) improve residual networks by introducing learnable mixing across multiple residual streams, but unconstrained mixing leads to tra

The Matching Principle: A Geometric Theory of Loss Functions for Nuisance-Robust Representation Learning

arXiv:2605.22800v1 Announce Type: new Abstract: Robustness, domain adaptation, photometric and occlusion invariance, compositional generalisation, temporal robustness, alignment safety, and classical

The Value of Covariance Matching in Gaussian DDPMs and the Lanczos Sampler

arXiv:2605.22723v1 Announce Type: new Abstract: A central error measure in Gaussian DDPMs is the path-space KL divergence between the exact reverse chain and the learned Gaussian reverse process. This

When Stronger Triggers Backfire: A High-Dimensional Theory of Backdoor Attacks

arXiv:2605.22481v1 Announce Type: new Abstract: Backdoor poisoning attacks behave counter-intuitively in high dimensions: stronger training triggers can help the defender. We study regularised general

4D-GSW: Kinematic-Aware Spatio-Temporal Consistent Watermarking for 4D Gaussian Splatting

arXiv:2605.22342v1 Announce Type: new Abstract: While 4D Gaussian Splatting (4DGS) has revolutionized high-fidelity dynamic reconstruction, safeguarding the intellectual property of these assets remai

researcharxiv-cs-cv

4D Radar Semantic Segmentation of People in Field Conditions Using Temporal Multi-View Networks

arXiv:2404.05307v2 Announce Type: replace Abstract: Reliable people detection is crucial for the safe autonomy of mobile robots and heavy vehicles, both on roads and in industrial settings like mining

applicationsarxiv-cs-cv

A Robust Semantic Segmentation Pipeline for the CVPR 2026 8th UG2+ Challenge Track 2

arXiv:2605.22216v1 Announce Type: new Abstract: This report presents our solution for the WeatherProof Dataset Challenge, namely CVPR 2026 8th UG2+ Challenge Track 2: Semantic Segmentation in Adverse

researcharxiv-cs-cv

Agentic Agile-V: From Vibe Coding to Verified Engineering in Software and Hardware Development

arXiv:2605.20456v1 Announce Type: cross Abstract: Agentic AI coding systems can inspect repositories, plan implementation steps, edit files, call tools, run tests, and submit pull requests. These capa

agentsarxiv-cs-ai

An Entity Linking Agent for Question Answering

arXiv:2508.03865v4 Announce Type: replace Abstract: Some Question Answering (QA) systems rely on knowledge bases (KBs) to provide accurate answers. Entity Linking (EL) plays a critical role in linking

agentsarxiv-cs-cl

AtomicMotion: Learning Human Motion From Different Human Parts

arXiv:2605.22631v1 Announce Type: new Abstract: Accurately reconstructing full-body poses from sparse head and hand trajectories is a foundational challenge for immersive AR/VR telepresence. Current m

local-aiarxiv-cs-cv

b9283

local-aillama-cpp-releases

Release b9283 of llama.cpp includes updates to the BPE tokenizer with new pre-type dispatch and Carbon-3B DNA tokenizer support, along with refactoring of tokenizer helpers to follow project conventio

b9286

local-aillama-cpp-releases

B9286 introduces support for HybridDNATokenizer as its own vocabulary type (LLAMA_VOCAB_TYPE_HYBRIDDNA), enabling proper tokenization of DNA sequences by routing raw text through a DNA-aware splitter

Beyond Pixels: Learning Invariant Rewards for Real-World Robotics From a Few Demonstrations

arXiv:2605.22123v1 Announce Type: new Abstract: Designing reward functions that generalize beyond controlled laboratory settings remains a fundamental challenge in reinforcement learning for robotics.

safetyarxiv-cs-ro

Bounding-Box Trajectories Matter for Video Anomaly Detection

arXiv:2605.21957v1 Announce Type: new Abstract: Video anomaly detection is critical for public safety and security, yet remains highly challenging despite extensive research due to large variations in

safetyarxiv-cs-cv

Broadening Access to Transportation Safety Data with Generative AI: A Schema-Grounded Framework for Spatial Natural Language Queries

arXiv:2605.21712v1 Announce Type: new Abstract: Transportation safety analysis requires integrating crash records, roadway attributes, and geospatial data through GIS-based workflows, but access remai

local-aiarxiv-cs-cl

Cell Phantom Video Generation in Elliptical Fourier Descriptor Domain

arXiv:2605.22563v1 Announce Type: new Abstract: Training Deep Neural Networks for tracking individual cells in biomedical videos requires a large amount of annotated data. The annotation of videos for

researcharxiv-cs-cv

Chinese sensorimotor and embodiment norms for 3,000 lexicalized concepts

arXiv:2605.22616v1 Announce Type: new Abstract: Understanding how conceptual knowledge is grounded in bodily experience, and to what extent machine systems can acquire such knowledge without direct se

researcharxiv-cs-cl

COAgents: Multi-Agent Framework to Learn and Navigate Routing Problems Search Space

arXiv:2605.20618v1 Announce Type: new Abstract: Although Vehicle Routing Problems (VRP) are essential to many real-world systems, they remain computationally intractable at scale due to their combinat

agentsarxiv-cs-ai

Diagnosis Is Not Prescription: Linguistic Co-Adaptation Explains Patching Hazards in LLM Pipelines

arXiv:2605.21958v1 Announce Type: new Abstract: When a multi-module LLM agent fails, the module most responsible for the failure is not necessarily the best place to intervene. We demonstrate this Dia

safetyarxiv-cs-cl

Diffusion-guided Generalizable Enhancer for Urban Scene Reconstruction

arXiv:2605.22420v1 Announce Type: new Abstract: Urban scene reconstruction from real-world observations has emerged as a powerful tool for self-driving development and testing. While current neural re

agentsarxiv-cs-cv