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Pushing Radar Odometry Beyond the Pavement: Current Capabilities and Challenges

arXiv:2604.24674v1 Announce Type: new Abstract: Radar offers unique advantages for localization in unstructured environments, including robustness to weather, lighting, and airborne particulates. Whil

researcharxiv-cs-ro

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PushupBench: Your VLM is not good at counting pushups

DGX agent

arXiv:2604.23407v1 Announce Type: cross Abstract: Large vision-language models (VLMs) can recognize extit{what} happens in video but fail to count extit{how many} times. We introduce extbf{PushupBench

researcharxiv-cs-ai

28 Apr 2026

QED: An Open-Source Multi-Agent System for Generating Mathematical Proofs on Open Problems

arXiv:2604.24021v1 Announce Type: new Abstract: We explore a central question in AI for mathematics: can AI systems produce original, nontrivial proofs for open research problems? Despite strong bench

QEVA: A Reference-Free Evaluation Metric for Narrative Video Summarization with Multimodal Question Answering

arXiv:2604.24052v1 Announce Type: cross Abstract: Video-to-text summarization remains underexplored in terms of comprehensive evaluation methods. Traditional n-gram overlap-based metrics and recent la

Applications

Quantifying and Improving the Robustness of Retrieval-Augmented Language Models Against Spurious Features in Grounding Data

arXiv:2503.05587v3 Announce Type: replace-cross Abstract: Robustness has become a critical attribute for the deployment of RAG systems in real-world applications. Existing research focuses on robustne

applicationsarxiv-cs-ai

Quantifying and Mitigating Self-Preference Bias of LLM Judges

arXiv:2604.22891v1 Announce Type: cross Abstract: LLM-as-a-Judge has become a dominant approach in automated evaluation systems, playing critical roles in model alignment, leaderboard construction, qu

safetyarxiv-cs-ai

Quantifying Divergence in Inter-LLM Communication Through API Retrieval and Ranking

arXiv:2604.22760v1 Announce Type: cross Abstract: Large language models (LLMs) increasingly operate as autonomous agents that reason over external APIs to perform complex tasks. However, their reliabi

safetyarxiv-cs-ai

Quantum Kernel Advantage over Classical Collapse in Medical Foundation Model Embeddings

arXiv:2604.24597v1 Announce Type: cross Abstract: We provide evidence of quantum kernel advantage under noiseless simulation in binary insurance classification on MIMIC-CXR chest radiographs using qua

researcharxiv-cs-ai

Quantum Knowledge Graph: Modeling Context-Dependent Triplet Validity

arXiv:2604.23972v1 Announce Type: cross Abstract: Knowledge graphs (KGs) are increasingly used to support large lan guage model (LLM) reasoning, but standard triplet-based KGs treat each relation as g

Quasi-Equivariant Metanetworks

model-releasesarxiv-cs-lg

arXiv:2604.23720v1 Announce Type: new Abstract: Metanetworks are neural architectures designed to operate directly on pretrained weights to perform downstream tasks. However, the parameter space serve

Quasi-Quadratic Gradient: A New Direction for Accelerating the BFGS Method in Quasi-Newton Optimization

arXiv:2604.23922v1 Announce Type: cross Abstract: In this paper, we introduce the Quasi-Quadratic Gradient (QQG), a novel search direction designed to accelerate the BFGS method within the quasi-Newto

researcharxiv-cs-ai

Query2Diagram: Answering Developer Queries with UML Diagrams

arXiv:2604.23816v1 Announce Type: cross Abstract: Software documentation frequently becomes outdated or fails to exist entirely, yet developers need focused views of their codebase to understand compl

researcharxiv-cs-ai

Question-Adaptive Graph Learning for Multi-hop Retrieval Augmented Generation

arXiv:2510.11541v2 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) has demonstrated its ability to enhance Large Language Models (LLMs) by integrating external knowledge so

QuietWalk: Physics-Informed Reinforcement Learning for Ground Reaction Force-Aware Humanoid Locomotion Under Diverse Footwear

arXiv:2604.23702v1 Announce Type: new Abstract: Humanoid robots operating in human-centered environments (e.g., homes, hospitals, and offices) must mitigate foot--ground impact transients, as impact-i

safetyarxiv-cs-ro

RACANet: Reliability-Aware Crowd Anchor Network for RGB-T Crowd Counting

model-releasesarxiv-cs-cv

arXiv:2604.24543v1 Announce Type: new Abstract: RGB-Thermal (T) crowd counting aims to integrate visible-spectrum and thermal infrared information to improve the robustness of crowd density estimation

Radial Load--Reserve Certificates for Wasserstein Propagation in Isotropic Diffusion Samplers

arXiv:2603.19670v3 Announce Type: replace Abstract: Nonasymptotic diffusion analyses often decompose sampling error into score estimation, continuous reverse-time propagation, discretization, and term

researcharxiv-cs-lg

Local Ai

RADIANT-LLM: an Agentic Retrieval Augmented Generation Framework for Reliable Decision Support in Safety-Critical Nuclear Engineering

arXiv:2604.22755v1 Announce Type: cross Abstract: Reliable decision support in nuclear engineering requires traceable, domain-grounded knowledge retrieval, yet safety and risk analysis workflows remai

local-aiarxiv-cs-ai

Radiomics- and Clinical Feature-Driven Prediction of Volumetric Response in Skull-Base Meningioma after CyberKnife Radiosurgery

arXiv:2604.24230v1 Announce Type: new Abstract: Skull-base meningiomas are often characterized by favorable long-term prognosis, yet their anatomical complexity and proximity to critical neurovascular

researcharxiv-cs-cv

Rank, Head-Channel Non-Identifiability, and Symmetry Breaking: A Precise Analysis of Representational Collapse in Transformers

model-releasesarxiv-cs-cl

arXiv:2604.23681v1 Announce Type: cross Abstract: A widely cited result by Dong et al. (2021) showed that Transformers built from self-attention alone, without skip connections or feed-forward layers,

RAS: a Reliability Oriented Metric for Automatic Speech Recognition

arXiv:2604.24278v1 Announce Type: cross Abstract: Automatic speech recognition systems often produce confident yet incorrect transcriptions under noisy or ambiguous conditions, which can be misleading

RAT: RunAnyThing via Fully Automated Environment Configuration

arXiv:2604.23190v1 Announce Type: cross Abstract: Automating repository-level software engineering tasks is a foundational challenge for autonomous code agents, largely due to the difficulty of config

RaV-IDP: A Reconstruction-as-Validation Framework for Faithful Intelligent Document Processing

arXiv:2604.23644v1 Announce Type: cross Abstract: Intelligent document processing pipelines extract structured entities (tables, images, and text) from documents for use in downstream systems such as

RCSB PDB AI Help Desk: retrieval-augmented generation for protein structure deposition support

arXiv:2604.22800v1 Announce Type: cross Abstract: Motivation: Structural Biologists have contributed more than 245,000 experimentally determined three-dimensional structures of biological macromolecul

Reading in the Dark: Low-light Scene Text Recognition

model-releasesarxiv-cs-cv

arXiv:2604.23685v1 Announce Type: new Abstract: Accurate text recognition in low-light environments is essential for intelligent systems in applications ranging from autonomous vehicles to smart surve

Real-Time Non-Contact Force Compensation for Wrist-Mounted Force/Torque Sensors in Haptic-Enabled Robotic Surgery Training

arXiv:2604.23696v1 Announce Type: new Abstract: Haptic feedback has been a long-missed feature in robotic-assisted surgery, one that would allow surgeons to perceive tissue properties and apply contro

safetyarxiv-cs-ro

Real-time windrow detection from onboard tractor sensors for automated following

model-releasesarxiv-cs-ro

arXiv:2604.24628v1 Announce Type: new Abstract: Proprietary design in commercial windrow-detection systems restricts transparency and limits progress in open autonomous forage-harvesting research. We

RealFin: How Well Do LLMs Reason About Finance When Users Leave Things Unsaid?

arXiv:2602.07096v2 Announce Type: replace-cross Abstract: Reliable financial reasoning requires knowing not only how to answer, but also when an answer cannot be justified. In real financial practice,

Reasonably reasoning AI agents can avoid game-theoretic failures in zero-shot, provably

arXiv:2603.18563v2 Announce Type: replace Abstract: As autonomous AI agents increasingly mediate online platform markets, a fundamental question emerges: do these markets generate stable strategic out

Reclaiming Residual Knowledge: A Novel Paradigm to Low-Bit Quantization

arXiv:2408.00923v2 Announce Type: replace-cross Abstract: This paper explores a novel paradigm in low-bit (i.e. 4-bits or lower) quantization, differing from existing state-of-the-art methods, by fram

Agents

Reconstructive Authority Model: Runtime Execution Validity Under Partial Observability

arXiv:2604.22898v1 Announce Type: cross Abstract: Autonomous systems increasingly operate under partial observability where execution-relevant state is never fully accessible. Existing governance mech

agentsarxiv-cs-ai

RecoverFormer: End-to-End Contact-Aware Recovery for Humanoid Robots

arXiv:2604.22911v1 Announce Type: new Abstract: Humanoid robots operating in unstructured environments must recover from unexpected disturbances-a capability that remains challenging for end-to-end co

safetyarxiv-cs-ro

Applications

RedParrot: Accelerating NL-to-DSL for Business Analytics via Query Semantic Caching

arXiv:2604.22758v1 Announce Type: cross Abstract: Recently, at Xiaohongshu, the rapid expansion of e-commerce and advertising demands real-time business analytics with high accuracy and low latency. T

applicationsarxiv-cs-ai

Reducing Redundancy in Retrieval-Augmented Generation through Chunk Filtering

arXiv:2604.24334v1 Announce Type: new Abstract: Standard Retrieval-Augmented Generation (RAG) chunking methods often create excessive redundancy, increasing storage costs and slowing retrieval. This s

researcharxiv-cs-cl

RefEvo: Agentic Design with Co-Evolutionary Verification for Agile Reference Model Generation

arXiv:2604.24218v1 Announce Type: cross Abstract: As the complexity of System-on-Chip (SoC) designs grows, the shift-left paradigm necessitates the rapid development of high-fidelity reference models

ReFinE: Streamlining UI Mockup Iteration with Research Findings

arXiv:2604.04353v2 Announce Type: replace-cross Abstract: Although HCI research papers offer valuable design insights, designers often struggle to apply them in design workflows due to difficulties in

Reflective Flow Sampling Enhancement

arXiv:2603.06165v2 Announce Type: replace-cross Abstract: The growing demand for text-to-image generation has led to rapid advances in generative modeling. Recently, text-to-image diffusion models tra

safetyarxiv-cs-ai

RegMean++: Enhancing Effectiveness and Generalization of Regression Mean for Model Merging

arXiv:2508.03121v3 Announce Type: replace Abstract: Regression Mean (RegMean), an approach that formulates model merging as a linear regression problem, aims to find the optimal weights for each linea

researcharxiv-cs-lg

Reheat Nachos for Dinner? Evaluating AI Support for Cross-Cultural Communication of Neologisms

arXiv:2604.23842v1 Announce Type: cross Abstract: Neologisms and emerging slang are central to daily conversation, yet challenging for non-native speakers (NNS) to interpret and use appropriately in c

Reinforcement Learning with Backtracking Feedback

arXiv:2602.08377v2 Announce Type: replace-cross Abstract: Addressing the critical need for robust safety in Large Language Models (LLMs), particularly against adversarial attacks and in-distribution e

Local Ai

Reliable Microservice Tail Latency Prediction via Decoupled Dual-Stream Learning and Gradient Modulation

arXiv:2508.01635v2 Announce Type: replace-cross Abstract: Microservice architectures enable scalable cloud-native applications; however, the distributed nature of these systems complicates the mainten

local-aiarxiv-cs-ai

Reparameterization through Coverings and Topological Weight Priors

arXiv:2604.23804v1 Announce Type: new Abstract: We generalise the reparameterization trick applied in variational autoencoders (VAEs) letting these have latent spaces of non-trivial topology - i.e. th

researcharxiv-cs-lg

Agents

Representation Homogeneity and Systemic Instability in AI-Dominated Financial Markets: A Structural Approach

arXiv:2604.22818v1 Announce Type: cross Abstract: This paper investigates how similarity in the informational representation of market states among Artificial Intelligence (AI) trading agents can gene

agentsarxiv-cs-ai

Representational Curvature Modulates Behavioral Uncertainty in Large Language Models

arXiv:2604.23985v1 Announce Type: new Abstract: In autoregressive large language models (LLMs), temporal straightening offers an account of how the next-token prediction objective shapes representatio

ResAF-Net: An Anchor-Free Attention-Based Network for Tree Detection and Agricultural Mapping in Palestine

arXiv:2604.23653v1 Announce Type: cross Abstract: Reliable agricultural data is essential for food security, land-use planning, and economic resilience, yet in Palestine, such data remains difficult t

Resolution scaling governs DINOv3 transfer performance in chest radiograph classification

arXiv:2510.07191v3 Announce Type: replace-cross Abstract: Self-supervised learning (SSL) has improved visual representation learning, but its value in chest radiography remains uncertain. DINOv3 exten

Local Ai

Resource-Constrained UAV-Based Weed Detection for Site-Specific Management on Edge Devices

arXiv:2604.23442v1 Announce Type: new Abstract: Weeds compete with crops for light, water, and nutrients, reducing yield and crop quality. Efficient weed detection is essential for site-specific weed

local-aiarxiv-cs-cv

Resource-Lean Lexicon Induction for German Dialects

model-releasesarxiv-cs-cl

arXiv:2604.23824v1 Announce Type: new Abstract: Automatic induction of high-quality dictionaries is essential for building lexical resources, yet low-resource languages and dialects pose several chall

Rethinking Parameter Sharing for LLM Fine-Tuning with Multiple LoRAs

arXiv:2509.25414v2 Announce Type: replace-cross Abstract: Large language models are often adapted using parameter-efficient techniques such as Low-Rank Adaptation (LoRA), formulated as y = W_0x + BAx,