Search: “papers”

'Don't Do That!': Guiding Embodied Systems through Large Language Model-based Constraint Generation

arXiv:2506.04500v3 Announce Type: replace-cross Abstract: Recent advancements in large language models (LLMs) have spurred interest in robotic navigation that incorporates complex spatial, mathematica

researcharxiv-cs-ro

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Model Releases

DROP: Distributional and Regular Optimism and Pessimism for Reinforcement Learning

DGX agent

arXiv:2410.17473v2 Announce Type: replace Abstract: In reinforcement learning (RL), temporal difference (TD) error is known to be related to the firing rate of dopamine neurons. It has been observed t

model-releasesarxiv-cs-lg

10 Apr 2026

E-3DPSM: A State Machine for Event-Based Egocentric 3D Human Pose Estimation

arXiv:2604.08543v1 Announce Type: new Abstract: Event cameras offer multiple advantages in monocular egocentric 3D human pose estimation from head-mounted devices, such as millisecond temporal resolut

Efficient Provably Secure Linguistic Steganography via Range Coding

arXiv:2604.08052v1 Announce Type: new Abstract: Linguistic steganography involves embedding secret messages within seemingly innocuous texts to enable covert communication. Provable security, which is

Tutorials

ELC: Evidential Lifelong Classifier for Uncertainty Aware Radar Pulse Classification

arXiv:2604.06958v1 Announce Type: cross Abstract: Reliable radar pulse classification is essential in Electromagnetic Warfare for situational awareness and decision support. Deep Neural Networks have

tutorialsarxiv-cs-lg

EMMa: End-Effector Stability-Oriented Mobile Manipulation for Tracked Rescue Robots

arXiv:2604.08292v1 Announce Type: new Abstract: The autonomous operation of tracked mobile manipulators in rescue missions requires not only ensuring the reachability and safety of robot motion but al

safetyarxiv-cs-ro

Extracting Breast Cancer Phenotypes from Clinical Notes: Comparing LLMs with Classical Ontology Methods

arXiv:2604.06208v1 Announce Type: cross Abstract: A significant amount of data held in Oncology Electronic Medical Records (EMRs) is contained in unstructured provider notes -- including but not limit

FedSpy-LLM: Towards Scalable and Generalizable Data Reconstruction Attacks from Gradients on LLMs

model-releasesarxiv-cs-lg

arXiv:2604.06297v1 Announce Type: cross Abstract: Given the growing reliance on private data in training Large Language Models (LLMs), Federated Learning (FL) combined with Parameter-Efficient Fine-Tu

FIT: A Large-Scale Dataset for Fit-Aware Virtual Try-On

model-releasesarxiv-cs-cv

arXiv:2604.08526v1 Announce Type: new Abstract: Given a person and a garment image, virtual try-on (VTO) aims to synthesize a realistic image of the person wearing the garment, while preserving their

FLeX: Fourier-based Low-rank EXpansion for multilingual transfer

arXiv:2604.06253v1 Announce Type: cross Abstract: Cross-lingual code generation is critical in enterprise environments where multiple programming languages coexist. However, fine-tuning large language

Force-Aware Residual DAgger via Trajectory Editing for Precision Insertion with Impedance Control

arXiv:2603.04038v2 Announce Type: replace Abstract: Imitation learning (IL) has shown strong potential for contact-rich precision insertion tasks. However, its practical deployment is often hindered b

safetyarxiv-cs-ro

From experimentation to engagement: on the paradox of participatory AI and power in contexts of forced displacement and humanitarian crises

arXiv:2604.06219v1 Announce Type: cross Abstract: Across the Global North, calls for participatory artificial intelligence (AI) to improve the responsible, safe, and ethical use of AI have increased,

From Ground Truth to Measurement: A Statistical Framework for Human Labeling

arXiv:2604.07591v1 Announce Type: cross Abstract: Supervised machine learning assumes that labeled data provide accurate measurements of the concepts models are meant to learn. Yet in practice, human

Front-End Ethics for Sensor-Fused Health Conversational Agents: An Ethical Design Space for Biometrics

arXiv:2604.06203v1 Announce Type: cross Abstract: The integration of continuous data from built-in sensors and Large Language Models (LLMs) has fueled a surge of 'Sensor-Fused LLM agents' for personal

Hardware

Full State-Space Visualisation of the 8-Puzzle: Feasibility, Design, and Educational Use

arXiv:2604.06186v1 Announce Type: cross Abstract: Search algorithms are a foundational topic in artificial intelligence education, yet even simple domains can generate large state spaces that challeng

hardwarearxiv-cs-ai

Great to see this on X. This is something I created during my PhD time 20 years ago.

Great to see this on X. This is something I created during my PhD time 20 years ago. This is a healing grid by Japanese artist Ryota Kanai. If you stare at the center, the irregularities start to heal

researchdavid-ha--x

Guaranteeing Knowledge Integration with Joint Decoding for Retrieval-Augmented Generation

arXiv:2604.08046v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) significantly enhances Large Language Models (LLMs) by providing access to external knowledge. However, current res

Guardian-as-an-Advisor: Advancing Next-Generation Guardian Models for Trustworthy LLMs

arXiv:2604.07655v1 Announce Type: cross Abstract: Hard-gated safety checkers often over-refuse and misalign with a vendor's model spec; prevailing taxonomies also neglect robustness and honesty, yield

HCRE: LLM-based Hierarchical Classification for Cross-Document Relation Extraction with a Prediction-then-Verification Strategy

arXiv:2604.07937v1 Announce Type: new Abstract: Cross-document relation extraction (RE) aims to identify relations between the head and tail entities located in different documents. Existing approache

Hierarchical Feature Learning for Medical Point Clouds via State Space Model

arXiv:2504.13015v3 Announce Type: replace Abstract: Deep learning-based point cloud modeling has been widely investigated as an indispensable component of general shape analysis. Recently, transformer

Applications

High-Precision Estimation of the State-Space Complexity of Shogi via the Monte Carlo Method

arXiv:2604.06189v1 Announce Type: new Abstract: Determining the state-space complexity of the game of Shogi (Japanese Chess) has been a challenging problem, with previous combinatorial estimates leavi

applicationsarxiv-cs-ai

HingeMem: Boundary Guided Long-Term Memory with Query Adaptive Retrieval for Scalable Dialogues

arXiv:2604.06845v1 Announce Type: cross Abstract: Long-term memory is critical for dialogue systems that support continuous, sustainable, and personalized interactions. However, existing methods rely

HistDiT: A Structure-Aware Latent Conditional Diffusion Model for High-Fidelity Virtual Staining in Histopathology

model-releasesarxiv-cs-cv

arXiv:2604.08305v1 Announce Type: cross Abstract: Immunohistochemistry (IHC) is essential for assessing specific immune biomarkers like Human Epidermal growth-factor Receptor 2 (HER2) in breast cancer

HumanLLM: Benchmarking and Improving LLM Anthropomorphism via Human Cognitive Patterns

arXiv:2601.10198v3 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities in reasoning and generation, serving as the foundation for advanced persona s

Hybrid CNN-Transformer Architecture for Arabic Speech Emotion Recognition

arXiv:2604.07357v1 Announce Type: new Abstract: Recognizing emotions from speech using machine learning has become an active research area due to its importance in building human-centered applications

Inference-Time Code Selection via Symbolic Equivalence Partitioning

arXiv:2604.06485v1 Announce Type: cross Abstract: 'Best-of-N' selection is a popular inference-time scaling method for code generation using Large Language Models (LLMs). However, to reliably identify

Information as Structural Alignment: A Dynamical Theory of Continual Learning

arXiv:2604.07108v1 Announce Type: cross Abstract: Catastrophic forgetting is not an engineering failure. It is a mathematical consequence of storing knowledge as global parameter superposition. Existi

Karma Mechanisms for Decentralised, Cooperative Multi Agent Path Finding

arXiv:2604.07970v1 Announce Type: cross Abstract: Multi-Agent Path Finding (MAPF) is a fundamental coordination problem in large-scale robotic and cyber-physical systems, where multiple agents must co

safetyarxiv-cs-ro

Knowledge Graphs Generation from Cultural Heritage Texts: Combining LLMs and Ontological Engineering for Scholarly Debates

arXiv:2511.10354v1 Announce Type: cross Abstract: Cultural Heritage texts contain rich knowledge that is difficult to query systematically due to the challenges of converting unstructured discourse in

Lang2Act: Fine-Grained Visual Reasoning through Self-Emergent Linguistic Toolchains

arXiv:2602.13235v2 Announce Type: replace-cross Abstract: Visual Retrieval-Augmented Generation (VRAG) enhances Vision-Language Models (VLMs) by incorporating external visual documents to address a gi

Latent Anomaly Knowledge Excavation: Unveiling Sparse Sensitive Neurons in Vision-Language Models

arXiv:2604.07802v1 Announce Type: new Abstract: Large-scale vision-language models (VLMs) exhibit remarkable zero-shot capabilities, yet the internal mechanisms driving their anomaly detection (AD) pe

LLM-based Schema-Guided Extraction and Validation of Missing-Person Intelligence from Heterogeneous Data Sources

arXiv:2604.06571v1 Announce Type: cross Abstract: Missing-person and child-safety investigations rely on heterogeneous case documents, including structured forms, bulletin-style posters, and narrative

Looking Beyond the Obvious: A Survey on Abstract Concept Recognition for Video Understanding

arXiv:2508.20765v2 Announce Type: replace-cross Abstract: The automatic understanding of video content is advancing rapidly. Empowered by deeper neural networks and large datasets, machines are increa

LoRA-DA: Data-Aware Initialization for Low-Rank Adaptation via Asymptotic Analysis

arXiv:2510.24561v2 Announce Type: replace-cross Abstract: LoRA has become a widely adopted method for PEFT, and its initialization methods have attracted increasing attention. However, existing method

Lost in the Hype: Revealing and Dissecting the Performance Degradation of Medical Multimodal Large Language Models in Image Classification

arXiv:2604.08333v1 Announce Type: new Abstract: The rise of multimodal large language models (MLLMs) has sparked an unprecedented wave of applications in the field of medical imaging analysis. However

LumiCtrl : Learning Illuminant Prompts for Lighting Control in Personalized Text-to-Image Models

arXiv:2512.17489v2 Announce Type: replace Abstract: Text-to-image (T2I) models have demonstrated remarkable progress in creative image generation, yet they still lack precise control over scene illumi

Applications

Luwen Technical Report

arXiv:2604.06737v1 Announce Type: cross Abstract: Large language models have demonstrated remarkable capabilities across a wide range of natural language processing tasks, yet their application in the

applicationsarxiv-cs-ai

MARCH: Evaluating the Intersection of Ambiguity Interpretation and Multi-hop Inference

model-releasesarxiv-cs-cl

arXiv:2509.22750v3 Announce Type: replace Abstract: Real-world multi-hop QA is naturally linked with ambiguity, where a single query can trigger multiple reasoning paths that require independent resol

Agents

MedRoute: RL-Based Dynamic Specialist Routing in Multi-Agent Medical Diagnosis

arXiv:2604.06180v1 Announce Type: cross Abstract: Medical diagnosis using Large Multimodal Models (LMMs) has gained increasing attention due to capability of these models in providing precise diagnose

agentsarxiv-cs-lg

MemReader: From Passive to Active Extraction for Long-Term Agent Memory

arXiv:2604.07877v1 Announce Type: new Abstract: Long-term memory is fundamental for personalized and autonomous agents, yet populating it remains a bottleneck. Existing systems treat memory extraction

MF-GLaM: A multifidelity stochastic emulator using generalized lambda models

model-releasesarxiv-cs-lg

arXiv:2507.10303v2 Announce Type: replace-cross Abstract: Stochastic simulators exhibit intrinsic stochasticity due to unobservable, uncontrollable, or unmodeled input variables, resulting in random o

Mixture Proportion Estimation and Weakly-supervised Kernel Test for Conditional Independence

arXiv:2604.07191v1 Announce Type: cross Abstract: Mixture proportion estimation (MPE) aims to estimate class priors from unlabeled data. This task is a critical component in weakly supervised learning

Modernizing Amdahl's Law: How AI Scaling Laws Shape Computer Architecture

arXiv:2603.20654v4 Announce Type: replace-cross Abstract: Classical Amdahl's Law conceptualized the limit of speedup for an era of fixed serial-parallel decomposition and homogeneous replication. Mode

Monocular Depth Estimation From the Perspective of Feature Restoration: A Diffusion Enhanced Depth Restoration Approach

model-releasesarxiv-cs-cv

arXiv:2604.07664v1 Announce Type: new Abstract: Monocular Depth Estimation (MDE) is a fundamental computer vision task with important applications in 3D vision. The current mainstream MDE methods empl

Multi-modal user interface control detection using cross-attention

arXiv:2604.06934v1 Announce Type: cross Abstract: Detecting user interface (UI) controls from software screenshots is a critical task for automated testing, accessibility, and software analytics, yet

Agents

NaviSlim: Adaptive Context-Aware Navigation and Sensing via Dynamic Slimmable Networks

arXiv:2407.01563v2 Announce Type: replace Abstract: Small-scale autonomous airborne vehicles, such as micro-drones, are expected to be a central component of a broad spectrum of applications ranging f

agentsarxiv-cs-ro

Agents

NaviSplit: Dynamic Multi-Branch Split DNNs for Efficient Distributed Autonomous Navigation

arXiv:2406.13086v2 Announce Type: replace Abstract: Lightweight autonomous unmanned aerial vehicles (UAV) are emerging as a central component of a broad range of applications. However, autonomous navi

agentsarxiv-cs-ro

Hardware

NestPipe: Large-Scale Recommendation Training on 1,500+ Accelerators via Nested Pipelining

arXiv:2604.06956v1 Announce Type: cross Abstract: Modern recommendation models have increased to trillions of parameters. As cluster scales expand to O(1k), distributed training bottlenecks shift from

hardwarearxiv-cs-lg