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CLIPPER: Replayable Shortlisted Optimization for Repeated Spatial Coverage Planning

arXiv:2608.26819v1 Announce Type: new Abstract: Operational requirements developed with the City of Braunschweig frame municipal micromobility planning under geofenced exclusions, mandatory retained s

safetyarxiv-cs-ro

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Closing the Loop on the Poppy Humanoid: Bipedal Locomotion with Linear-Quadratic Control and Learned Cost Functions

DGX agent

arXiv:2608.26505v1 Announce Type: new Abstract: The Poppy Humanoid is an open-source, low-cost robot suitable for research and education in artificial intelligence. However, we are unaware of any publ

applicationsarxiv-cs-ro

28 Aug 2026

ClusterAttention: A training-free speedup of bidirectional attention

arXiv:2608.26965v1 Announce Type: cross Abstract: This paper introduces ClusterAttention, a general training-free speedup of bidirectional attention layers. Existing sparse attention methods either re

Co-Evolving Structured Knowledge and Reasoning in Language Models

arXiv:2608.26386v1 Announce Type: cross Abstract: Retrieval-augmented methods improve factual accuracy by grounding language models in external knowledge, but retrieving over unstructured text often i

CODE: Cross-Modal Calibration and Dynamic Suppression for Open World Object Detection

model-releasesarxiv-cs-cv

arXiv:2608.27214v1 Announce Type: new Abstract: Open World Object Detection (OWOD) built on multimodal foundation models often suffers from semantic ambiguity caused by unidirectional text-to-vision m

COFM: Consistent Optimal Transport Flow Matching via Partially Input Convex Neural Networks

model-releasesarxiv-cs-lg

arXiv:2511.06042v2 Announce Type: replace Abstract: Optimal transport (OT) provides a principled framework for learning mappings between probability distributions, and has found broad applications in

CoGeo-GS: Concept-Driven and Geometry-Aware Multi-Object Removal in 3D Scenes

arXiv:2608.26656v1 Announce Type: cross Abstract: Multi-object removal in 3D scenes is challenging due to severe occlusions, semantic entanglement, and the difficulty of maintaining geometric and mult

Common Geodesics Do Not Guarantee Fisher Consistency of the Structured SVM: Minimal Counterexamples and a Tree-Metric Classification

arXiv:2608.27203v1 Announce Type: new Abstract: A known necessary condition for Fisher consistency of the structured support vector machine requires the task loss to be a metric for which every output

Communication styles and reader preferences of LLM- and human-authored COVID-19 information explanations: a case study

arXiv:2505.08143v2 Announce Type: replace-cross Abstract: With the wide adoption of large language models (LLMs) in information assistance, it is essential to examine their alignment with human commun

Comparative Evaluation of 3D Reconstruction Methods for Immersive Visualization of Laboratory Objects

arXiv:2608.27301v1 Announce Type: cross Abstract: In this study, we examined whether current 3D reconstruction methods can support the creation of realistic holographic representations of laboratory o

Comparing Chunking and Embedding Strategies for Turkish RAG Systems

arXiv:2608.26192v1 Announce Type: cross Abstract: How documents are segmented into retrievable chunks and how those chunks are embedded strongly affect Retrieval-Augmented Generation (RAG) quality, ye

Compositional Generalization via Structural Identification in a Category-Theoretic Framework

arXiv:2608.26465v1 Announce Type: new Abstract: Compositional generalization is usually evaluated through model accuracy. We instead ask which structural or lexical identifications make held-out COGS

Applications

Compositional Online Learning for Semantic Data Processing Systems

arXiv:2608.27244v1 Announce Type: cross Abstract: An LLM call in a semantic data processing system is expensive enough to dominate query cost, yet slow enough to hide a CPU-side learner's update behin

applicationsarxiv-cs-ai

Cone Extended Rayleigh Quotients for Directed Graph Learning: Minimax Spectral Certificates, Sensitivity, and Adaptive Control

arXiv:2608.27122v1 Announce Type: new Abstract: Directed graph learning naturally leads to trainable nonsymmetric propagation operators with distinct right and left spectral structures. Building on th

Consolidating RLVR Capabilities Across Domains: A Deep Dive into Fusion Paradigms

model-releasesarxiv-cs-cl

arXiv:2608.27409v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) improves specific capabilities of large language models, but covering multiple capabilities often

Constraint-Aware Physics-Informed Neural Networks for Static Shape Estimation of Co-Manipulative Continuum Robots

arXiv:2608.26273v1 Announce Type: cross Abstract: Static shape estimation of co-manipulative continuum robots (CCRs) is challenging because the continuum arms and manipulated flexible object form a cl

Agents

Contact-Aided Factor-Graph Localization for Underwater Sampling

arXiv:2608.26932v1 Announce Type: new Abstract: Accurate state estimation for autonomous underwater vehicles performing close-range seafloor sampling remains challenging. In low-altitude operation, do

agentsarxiv-cs-ro

CorporateBench: Large-Scale Q&A Benchmarking with Temporal Knowledge Bases

model-releasesarxiv-cs-ai

arXiv:2608.27391v1 Announce Type: new Abstract: LLMs are increasingly able to answer complex questions about enterprise-scale document collections. But evaluation is hard: companies don't want to shar

Counterfactual Bias Testing for Application Tracking System

arXiv:2608.26899v1 Announce Type: new Abstract: Automated candidate-job matching systems are increasingly classified as high-risk AI under emerging regulation, yet auditing them for demographic bias i

CounterVid: Counterfactual Video Generation for Mitigating Action and Temporal Hallucinations in Video-Language Models

arXiv:2601.04778v2 Announce Type: replace-cross Abstract: Video-language models (VLMs) achieve strong multimodal understanding but remain prone to hallucinations, especially when reasoning about actio

CPGRec+: A Balance-oriented Framework for Personalized Video Game Recommendations

arXiv:2604.14586v4 Announce Type: replace-cross Abstract: The rapid expansion of gaming industry requires advanced recommender systems tailored to its dynamic landscape. Existing Graph Neural Network

CritICL: Inference-Time Weak-to-Strong Generalization from Small Language Model Failure Modes

arXiv:2608.27455v1 Announce Type: new Abstract: Recent advances in inference-time scaling have significantly improved the reasoning performance of large language models (LLMs). However, these methods

Cross-Architecture Knowledge Distillation from a Vision Foundation Model to a Lightweight Visual State Space Model for Tea Leaf Disease Classification

model-releasesarxiv-cs-cv

arXiv:2608.26771v1 Announce Type: new Abstract: Automated tea leaf disease classification supports precision agriculture, yet deploying accurate models on edge devices remains challenging under tight

Cross-Lingual Alignment Without Joint Training: Do Monolingual Language Models Converge on Universal Representations?

arXiv:2608.27115v1 Announce Type: new Abstract: Cross-lingual alignment in multilingual language models is typically attributed to joint training: shared parameters, mixed-language batches, or explici

safetyarxiv-cs-cl

Tutorials

Cross-lingual Representation Learning via Centroid Intervention Fusion

arXiv:2608.26357v1 Announce Type: new Abstract: Large language models (LLMs) exhibit uneven multilingual performance, especially when dealing with low-resource languages. Inference-time intervention o

tutorialsarxiv-cs-cl

Cross-Platform Benchmark of Neural 3D Reconstruction for Autonomous Laboratory Robots

model-releasesarxiv-cs-ro

arXiv:2608.26383v1 Announce Type: new Abstract: Autonomous robots performing laboratory tasks depend on 3D reconstruction pipelines that can turn raw camera streams into actionable object representati

Cross-Platform Generalisation Failure in Mental Health Natural Language Processing: A Five-Axis Fairness Audit of Transformer Models on Social Media

arXiv:2608.26138v1 Announce Type: new Abstract: We introduce the Cross-Platform Fairness Evaluation (CPFE) framework -- a five-axis audit protocol covering discriminative performance, calibration, sta

safetyarxiv-cs-cl

Cross-simulator transfer with foundation model summaries: Towards robust SKA-era reionization inference

model-releasesarxiv-cs-lg

arXiv:2608.26354v1 Announce Type: cross Abstract: Simulation-based inference (SBI) for parameter estimation is vulnerable to model misspecification: neural summaries and density estimators trained on

D2C-Routing: Dimension-to-Composition Evidence Routing for Mixed-Origin AI-Generated Text Detection

model-releasesarxiv-cs-cl

arXiv:2608.27380v1 Announce Type: new Abstract: AI-generated text detection is commonly framed as a binary document-level judgment about whether a text is human-written or machine-generated. This fram

Data-driven Koopman mode approximation: A neural power iteration algorithm

arXiv:2608.26943v1 Announce Type: cross Abstract: This paper proposes a novel data-driven algorithm to approximate the dominant eigenfunctions (aka.~modes) of the Koopman operator of nonlinear dynamic

Data-efficient crack quantification in lithium-ion cathodes using foundation model transfer

arXiv:2608.27162v1 Announce Type: cross Abstract: Battery lifetime is central to sustainable electrification, yet the particle cracking that drives lithium-ion cathode aging is hard to measure: quanti

Data Science Approaches to Evaluating Honours Candidates

arXiv:2608.26135v1 Announce Type: new Abstract: We present a modular data-science pipeline for estimating public sentiment towards individuals from fragmented, unstructured open-source intelligence (O

Agents

Daydreaming: Stealing Hidden Agent Skills through Black-Box Task Interaction

arXiv:2608.26733v1 Announce Type: cross Abstract: Agent skills bundle instructions, reference data, and executable helpers that let a general agent perform specialized tasks. Hosted providers can keep

agentsarxiv-cs-ai

Decay-Region Group Delay as a Forensic Cue for AI-Generated Impulsive Sounds

model-releasesarxiv-cs-ai

arXiv:2608.26346v1 Announce Type: cross Abstract: We investigate whether AI-generated impulsive sounds can be distinguished from real ones through group delay analysis. Our central finding is that AI-

Decentralized Multitask Learning over Learned Task Graphs

arXiv:2608.26989v1 Announce Type: new Abstract: This paper investigates decentralized multitask learning over networks when the underlying task relationships are unknown. While existing graph-regulari

Decoupled I/O-Dominant Pipelines for Large-Scale Whole-Slide Image Embedding Extraction

arXiv:2608.27278v1 Announce Type: cross Abstract: Whole-slide images (WSIs) are central to computational pathology but are prohibitively large, making patch-based processing the practical unit for fou

Decoupling Planning and Control for Instructable Agents

arXiv:2608.26788v1 Announce Type: new Abstract: Recent work shows that pre-trained, instruction-tuned vision-language models (VLMs) perform well at mapping from instructions and observations to high-l

DEEPCHART: How Far are LLMs from Faithful Data-Science Chart Generation?

model-releasesarxiv-cs-ai

arXiv:2608.26757v1 Announce Type: new Abstract: Faithful chart generation in real-world data-science workflows requires grounding visualizations in scattered evidence, computing chart-ready quantities

Tutorials

DeepPlanner: Scaling Planning Capability for Deep Research Agents via Advantage Shaping

arXiv:2510.12979v2 Announce Type: replace Abstract: Large language models (LLMs) augmented with multi-step reasoning and action generation abilities have shown promise in leveraging external tools to

tutorialsarxiv-cs-ai

DeflectBench: A Benchmark for Evaluating Rhetorical Fallacy Generation in LLMs

model-releasesarxiv-cs-cl

arXiv:2608.26119v1 Announce Type: new Abstract: Whether large language models can be prompted to generate rhetorical fallacies on demand, and whether current safety post-training constrains this behav

Dependency-Aware Revocable Decoding for Efficient Diffusion Large Language Model Inference

arXiv:2608.26574v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) offer a promising alternative to autoregressive generation by decoding multiple tokens in parallel through itera

Applications

Detection of Christmas tree plantations from high-resolution aerial imagery. A case study in the French Morvan

arXiv:2608.27290v1 Announce Type: new Abstract: Christmas tree plantations are economically relevant, yet a largely unexplored application domain in Remote Sensing (RS). Their delineation is challengi

applicationsarxiv-cs-cv

Applications

Diagnosing Conformal Prediction Failures Under Distribution Shift: A COVID-19 Case Study

arXiv:2601.00908v2 Announce Type: replace-cross Abstract: Conformal prediction provides distribution-free coverage guarantees, but these degrade under distribution shift - and practitioners lack tools

applicationsarxiv-cs-ai

Agents

Diff Mining: Logit Differences Reveal Finetuning Objectives

arXiv:2608.26462v1 Announce Type: cross Abstract: Finetuning has become the gold standard for refining existing behaviors and inducing new ones in language models, yet it often remains unclear exactly

agentsarxiv-cs-ai

Difference-in-Differences on a Censored Rating Scale Can Manufacture an Effect: Evidence from a Pre-Registered LLM-Judge Audit

arXiv:2608.27309v1 Announce Type: cross Abstract: Audits of LLM judges certify a bias by contrasting matched conditions, and the strongest designs difference twice: a within-item contrast between two

Differentiable Jitter Correction using Deep Learning-based Image Quality Metric for Phase-Contrast Micro-CT

arXiv:2608.27034v1 Announce Type: new Abstract: This paper proposes a fully differentiable jitter correction method for X-ray phase-contrast micro computed tomography using a deep learning-based image

Diffusion Policies for Short-Horizon Planning in Robot Crowd Navigation

model-releasesarxiv-cs-lg

arXiv:2608.27158v1 Announce Type: new Abstract: Robot crowd navigation requires safe and efficient decision-making under dense, dynamic, and multimodal human--robot interactions. Existing reinforcemen

DINOcular: Self-Supervised Visuospatial Representations

arXiv:2608.27226v1 Announce Type: new Abstract: We introduce a self-supervised framework for learning joint visuospatial representations from RGB-D observations. While modern vision foundation models