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The Last Human-Written Paper: Agent-Native Research Artifacts

arXiv:2604.24658v1 Announce Type: new Abstract: Scientific publication compresses a branching, iterative research process into a linear narrative, discarding the majority of what was discovered along

agentsarxiv-cs-lg

The Limits of Artificial Companionship

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arXiv:2604.23601v1 Announce Type: cross Abstract: This Article argues that conversations with companion chatbot should be subject to a clear structural distinction between commercial and non-commercia

applicationsarxiv-cs-cl

28 Apr 2026

The Optimal Sample Complexity of Multiclass and List Learning

model-releasesarxiv-cs-lg

arXiv:2604.24749v1 Announce Type: new Abstract: While the optimal sample complexity of binary classification in terms of the VC dimension is well-established, determining the optimal sample complexity

The Override Gap: A Magnitude Account of Knowledge Conflict Failure in Hypernetwork-Based Instant LLM Adaptation

arXiv:2604.23750v1 Announce Type: cross Abstract: Hypernetwork-based methods such as Doc-to-LoRA internalize a document into an LLM's weights in a single forward pass, but they fail systematically on

Tutorials

The Power of Power Law: Asymmetry Enables Compositional Reasoning

arXiv:2604.22951v1 Announce Type: new Abstract: Natural language data follows a power-law distribution, with most knowledge and skills appearing at very low frequency. While a common intuition suggest

tutorialsarxiv-cs-ai

The Pragmatic Persona: Discovering LLM Persona through Bridging Inference

arXiv:2604.24079v1 Announce Type: cross Abstract: Large Language Models (LLMs) reveal inherent and distinctive personas through dialogue. However, most existing persona discovery approaches rely on su

The Price of Agreement: Measuring LLM Sycophancy in Agentic Financial Applications

arXiv:2604.24668v1 Announce Type: new Abstract: Given the increased use of LLMs in financial systems today, it becomes important to evaluate the safety and robustness of such systems. One failure mode

The Randomness Floor: Measuring Intrinsic Non-Randomness in Language Model Token Distributions

arXiv:2604.22771v1 Announce Type: cross Abstract: Language models cannot be random. This paper introduces Entropic Deviation (ED), the normalised KL divergence between a model's token distribution and

The Rise of Large Language Models and the Direction and Impact of US Federal Research Funding

arXiv:2601.15485v2 Announce Type: replace-cross Abstract: Federal research funding shapes the direction, diversity, and impact of the US scientific enterprise. Large language models (LLMs) are rapidly

The Security Cost of Intelligence: AI Capability, Cyber Risk, and Deployment Paradox

arXiv:2604.23058v1 Announce Type: cross Abstract: Firms are deploying more capable AI systems, but organizational controls often have not kept pace. These systems can generate greater productivity gai

The Shape of Attraction in UMAP: Exploring the Embedding Forces in Dimensionality Reduction

arXiv:2503.09101v4 Announce Type: replace-cross Abstract: Uniform manifold approximation and projection (UMAP) is among the most popular neighbor embedding methods. The method samples pairs of point i

The Spectral Lifecycle of Transformer Training: Transient Compression Waves, Persistent Spectral Gradients, and the Q/K--V Asymmetry

arXiv:2604.22778v1 Announce Type: cross Abstract: We present the first systematic study of weight matrix singular value spectra during transformer pretraining, tracking full SVD decompositions of ever

The Surprising Effectiveness of Membership Inference with Simple N-Gram Coverage

model-releasesarxiv-cs-cl

arXiv:2508.09603v2 Announce Type: replace Abstract: Membership inference attacks serves as useful tool for fair use of language models, such as detecting potential copyright infringement and auditing

The Swarm Intelligence Freeway-Urban Trajectories (SWIFTraj) Dataset -- Part II: A Graph-Based Approach for Trajectory Connection

arXiv:2602.21954v2 Announce Type: replace-cross Abstract: In Part I of this companion paper series, we introduced SWIFTraj, a new open-source vehicle trajectory dataset collected using a unmanned aeri

safetyarxiv-cs-ro

Think Anywhere in Code Generation

arXiv:2603.29957v3 Announce Type: replace-cross Abstract: Recent advances in reasoning Large Language Models (LLMs) have primarily relied on upfront thinking, where reasoning occurs before final answe

agentsarxiv-cs-lg

Think-at-Hard: Selective Latent Iterations to Improve Reasoning Language Models

arXiv:2511.08577v2 Announce Type: replace-cross Abstract: Improving reasoning abilities of Large Language Models (LLMs), especially under parameter constraints, is crucial for real-world applications.

Thinking Like a Clinician: A Cognitive AI Agent for Clinical Diagnosis via Panoramic Profiling and Adversarial Debate

arXiv:2604.23605v1 Announce Type: new Abstract: The application of large language models (LLMs) in clinical decision support faces significant challenges of 'tunnel vision' and diagnostic hallucinatio

agentsarxiv-cs-ai

Time-Series Forecasting in Safety-Critical Environments: An EU-AI-Act-Compliant Open-Source Package / Zeitreihenprognose in sicherheitskritischen Umgebungen: Ein KI-VO-konformes Open-Source-Paket

arXiv:2604.23859v1 Announce Type: new Abstract: With spotforecast2-safe we present an integrated Compliance-by-Design approach to Python-based point forecasting of time series in safety-critical envir

safetyarxiv-cs-ai

TimingLLM: A Two-Stage Retrieval-Augmented Framework for Pre-Synthesis Timing Prediction from Verilog

arXiv:2604.23602v1 Announce Type: cross Abstract: Early, tool-free prediction of post-synthesis timing remains a key obstacle to rapid RTL iteration. We introduce TimingLLM, a two-stage retrieval-augm

researcharxiv-cs-lg

Token Is All You Price

arXiv:2510.09859v4 Announce Type: replace-cross Abstract: A seller of a dynamic information service under an information-throughput constraint screens buyers who privately differ in urgency. We charac

applicationsarxiv-cs-ai

Tutorials

TokenTrace: Multi-Concept Attribution through Watermarked Token Recovery

arXiv:2602.19019v2 Announce Type: replace Abstract: Generative AI models pose a significant challenge to intellectual property (IP), as they can replicate unique artistic styles and concepts without a

tutorialsarxiv-cs-cv

TOL: Textual Localization with OpenStreetMap

model-releasesarxiv-cs-cv

arXiv:2604.01644v2 Announce Type: replace Abstract: Natural language provides an intuitive way to express spatial intent in geospatial applications. While existing localization methods often rely on d

TopoHR: Hierarchical Centerline Representation for Cyclic Topology Reasoning in Driving Scenes with Point-to-Instance Relations

model-releasesarxiv-cs-cv

arXiv:2604.24119v1 Announce Type: new Abstract: Topology reasoning is crucial for autonomous driving. Current methods primarily focus on instance-level learning for centerline detection, followed by a

Touchless Intraoperative Image Access System Based on Vision-Based Hand Tracking

arXiv:2604.24235v1 Announce Type: new Abstract: Touchless interaction with medical images is becoming increasingly important in the surgical field, where sterility and continuity of the operational wo

researcharxiv-cs-cv

Toward Polymorphic Backdoor against Semantic Communication via Intensity-Based Poisoning

arXiv:2604.23231v1 Announce Type: cross Abstract: Semantic Communication (SC) backdoor attacks aim to utilize triggers to manipulate the system into producing predetermined outputs via backdoored shar

Toward Real-World Adoption of Portrait Relighting via Hybrid Domain Knowledge Fusion

arXiv:2604.23094v1 Announce Type: new Abstract: The real-world adoption of portrait relighting is hindered by dataset domain gaps, camera sensitivity, and computational costs. We address these challen

applicationsarxiv-cs-cv

Toward Theoretical Insights into Diffusion Trajectory Distillation via Operator Merging

arXiv:2505.16024v2 Announce Type: replace-cross Abstract: Diffusion trajectory distillation accelerates sampling by training a student model to approximate the multi-step denoising trajectories of a p

Towards Any-Quality Image Segmentation via Generative and Adaptive Latent Space Enhancement

arXiv:2601.02018v2 Announce Type: replace Abstract: Segment Anything Models (SAMs), known for their exceptional zero-shot segmentation performance, have garnered significant attention in the research

safetyarxiv-cs-cv

Towards Automated Ontology Generation from Unstructured Text: A Multi-Agent LLM Approach

arXiv:2604.23090v1 Announce Type: new Abstract: Automatically generating formal ontologies from unstructured natural language remains a central challenge in knowledge engineering. While large language

agentsarxiv-cs-ai

Towards Causally Interpretable Wi-Fi CSI-Based Human Activity Recognition with Discrete Latent Compression and LTL Rule Extraction

arXiv:2604.22979v1 Announce Type: new Abstract: We address Human Activity Recognition (HAR) utilizing Wi-Fi Channel State Information (CSI) under the joint requirements of causal interpretability, sym

Towards Continual Expansion of Data Coverage: Automatic Text-guided Edge-case Synthesis

arXiv:2509.26158v2 Announce Type: replace-cross Abstract: The performance of deep neural networks is strongly influenced by the quality of their training data. However, mitigating dataset bias by manu

Towards Fair and Robust Volumetric CT Classification via KL-Regularised Group Distributionally Robust Optimisation

arXiv:2603.15941v2 Announce Type: replace Abstract: Automated diagnosis from chest computed tomography (CT) scans faces two persistent challenges in clinical deployment: distribution shift across acqu

safetyarxiv-cs-cv

Towards High-Fidelity CAD Generation via LLM-Driven Program Generation and Text-Based B-Rep Primitive Grounding

arXiv:2603.11831v2 Announce Type: replace Abstract: The field of Computer-Aided Design (CAD) generation has made significant progress in recent years. Existing methods typically fall into two separate

applicationsarxiv-cs-cv

Towards Holistic Evaluation of Large Audio-Language Models: A Comprehensive Survey

arXiv:2505.15957v4 Announce Type: replace-cross Abstract: With advancements in large audio-language models (LALMs), which enhance large language models (LLMs) with auditory capabilities, these models

safetyarxiv-cs-ai

Towards Lawful Autonomous Driving: Deriving Scenario-Aware Driving Requirements from Traffic Laws and Regulations

arXiv:2604.24562v1 Announce Type: new Abstract: Driving in compliance with traffic laws and regulations is a basic requirement for human drivers, yet autonomous vehicles (AVs) can violate these requir

agentsarxiv-cs-ai

Towards Understanding the Expressive Power of GNNs with Global Readout

arXiv:2604.22870v1 Announce Type: cross Abstract: We study the expressive power of message-passing aggregate-combine-readout graph neural networks (ACR-GNNs). Particularly, we focus on the first-order

Trace2Skill: Distill Trajectory-Local Lessons into Transferable Agent Skills

arXiv:2603.25158v4 Announce Type: replace Abstract: Equipping Large Language Model (LLM) agents with domain-specific skills is critical for tackling complex tasks. Yet, manual authoring creates a seve

Training a General Purpose Automated Red Teaming Model

arXiv:2604.23067v1 Announce Type: cross Abstract: Automated methods for red teaming LLMs are an important tool to identify LLM vulnerabilities that may not be covered in static benchmarks, allowing fo

safetyarxiv-cs-cl

Training Machine Learning Models on Encrypted Data: A Privacy-Preserving Framework using Homomorphic Encryption

arXiv:2604.23245v1 Announce Type: cross Abstract: The use of Machine Learning (ML) for data-driven decision-making often relies on access to sensitive datasets, which introduces privacy challenges. Tr

applicationsarxiv-cs-ai

Trajectory Planning for an Articulated Commercial Vehicle using Model Predictive Contouring Control

arXiv:2604.24064v1 Announce Type: new Abstract: This paper presents a trajectory planning method for articulated commercial vehicles, specifically tractor-semitrailers, based on Model Predictive Conto

researcharxiv-cs-ro

Transferable Human Mobility Network Reconstruction with neuroGravity

arXiv:2604.23678v1 Announce Type: new Abstract: Accurate modeling of human mobility is critical for tackling urban planning and public health challenges. In undeveloped regions, the absence of compreh

Transferable Physical-World Adversarial Patches Against Object Detection in Autonomous Driving

arXiv:2604.23105v1 Announce Type: new Abstract: Deep learning drives major advances in autonomous driving (AD), where object detectors are central to perception. However, adversarial attacks pose sign

safetyarxiv-cs-cv

Transformer as an Euler Discretization of Score-based Variational Flow

arXiv:2604.23740v1 Announce Type: new Abstract: Despite the Transformer's dominance across machine learning, its architecture remains largely heuristic and lacks a unified theoretical foundation. We i

researcharxiv-cs-lg

Translate or Simplify First: An Analysis of Cross-lingual Text Simplification in English and French

arXiv:2604.23844v1 Announce Type: new Abstract: Cross-Lingual Text Simplification (CLTS) aims to make content more accessible across languages by simultaneously addressing both linguistic complexity a

researcharxiv-cs-cl

TRINITY: An Evolved LLM Coordinator

arXiv:2512.04695v3 Announce Type: replace Abstract: Combining diverse foundation models is promising, but weight-merging is limited by mismatched architectures and closed APIs. Trinity addresses this

researcharxiv-cs-lg

Triple-Phase Sequential Fusion Network for Hepatobiliary Phase Liver MRI Synthesis

arXiv:2604.22904v1 Announce Type: cross Abstract: Gadoxetate disodium-enhanced MRI is essential for the detection and characterization of hepatocellular carcinoma. However, acquisition of the hepatobi

researcharxiv-cs-cv

TSAssistant: A Human-in-the-Loop Agentic Framework for Automated Target Safety Assessment

arXiv:2604.23938v1 Announce Type: new Abstract: Target Safety Assessment (TSA) requires systematic integration of heterogeneous evidence, including genetic, transcriptomic, target homology, pharmacolo

safetyarxiv-cs-cl

Tube Diffusion Policy: Reactive Visual-Tactile Policy Learning for Contact-rich Manipulation

model-releasesarxiv-cs-ro

arXiv:2604.23609v1 Announce Type: new Abstract: Contact-rich manipulation is central to many everyday human activities, requiring continuous adaptation to contact uncertainty and external disturbances