Search: “papers”

arXiv:2608.17416v1 Announce Type: new Abstract: This paper addresses the multi-robot task allocation (MRTA) problem, which is essential for delivery and logistics applications. Our approach first defi

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Code as Representation: A Compilable Parsing Paradigm for Academic Documents

DGX agent

arXiv:2608.17550v1 Announce Type: cross Abstract: Academic papers are a primary carrier of scientific knowledge, yet most of this knowledge remains locked in PDFs that are optimized for human reading

model-releasesarxiv-cs-cl

19 Aug 2026

Diagonal Multi-omics Integration of Heterogenous Datasets

arXiv:2608.16968v1 Announce Type: cross Abstract: In this paper, we consider methods for the diagonal multi-omics integration of heterogeneous datasets. Several approaches to the nature of biological

Evaluating RL Explainability Methods by How Much They Help Fix Bugs in Agents

model-releasesarxiv-cs-lg

arXiv:2608.17524v1 Announce Type: new Abstract: This preliminary paper outlines a planned evaluation benchmark for Explainable Reinforcement Learning (XRL) methods. Current evaluations rely on functio

From Entity Mentions to Tone: An LLM-Based Pipeline for Media Bias Analysis

arXiv:2608.17454v1 Announce Type: new Abstract: This paper presents a pipeline for analyzing media bias and framing in online news. The pipeline groups articles into topics and events, adds named-enti

safetyarxiv-cs-cl

MSEditor: Toward Consistent Multi-Shot Video Editing

model-releasesarxiv-cs-cv

arXiv:2608.17559v1 Announce Type: new Abstract: In this paper, we tackle the problem of performing consistent, unified modifications to a multi-shot video sequence. This task is particularly challengi

Nonadaptive Learning in Robust Nonlinear Output Regulation

arXiv:2608.17262v1 Announce Type: cross Abstract: This paper considers robust nonadaptive regulation for general nonlinear systems in an output-feedback setting with arbitrarily high relative degree.

Optimizing Container Loading and Unloading through Dual-Cycling and Dockyard Rehandle Reduction Using a Hybrid Genetic Algorithm

arXiv:2406.08534v4 Announce Type: replace-cross Abstract: This paper addresses the NP-hard problem of optimizing container handling at ports by integrating Quay Crane Dual-Cycling (QCDC) and dockyard

Pessimistic Meta-Induction and Its Limits: Lessons from Frequentist Statistics and Machine Learning Theory

arXiv:2608.17213v1 Announce Type: new Abstract: This paper challenges the pessimistic meta-inductive argument against scientific realism by undermining its inductive step rather than its historical pr

Physics-Informed Sliding-Window Particle Filtering for Tactile-Only In-Hand 6-DoF Object Pose Refinement

arXiv:2608.17601v1 Announce Type: new Abstract: This paper studies tactile-only 6-DoF pose refinement and belief maintenance for grasped objects in static and short quasi-static in-hand configurations

Position: Fairness Failure in Generative Models is an Evaluation Problem

arXiv:2608.16974v1 Announce Type: cross Abstract: Despite groundbreaking advancements in generative models during the last decade, concerns about their lack of fairness, reinforcing societal inequalit

safetyarxiv-cs-ai

TabularQGAN: A quantum generative model for tabular data synthesis

arXiv:2505.22533v2 Announce Type: replace-cross Abstract: In this paper, we introduce a novel quantum generative model for synthesizing tabular data. Synthetic data is valuable in scenarios where real

applicationsarxiv-cs-ai

Token Optimization and Context Window Management in Multi-Agent AI Workflows

arXiv:2608.17188v1 Announce Type: cross Abstract: Multi-agent AI workflows are limited not only by model quality but by token cost, latency, and context-window quality. This paper presents a practitio

What If AI Carried Her Imagination? Black Girls as Creators in an AI Storytelling Weekend Program

arXiv:2608.16896v1 Announce Type: cross Abstract: This paper presents the design and outcomes of a seven-weekend AI storytelling program developed for Black girls aged 10-12. Grounded in Afrofuturism

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When will there be a frontier level llm with updateable engrams or fixed engrams?

model-releasesr-localllama

DeepSeek released on a paper on pretrained engrams in January. I’m surprised ds didn’t release engrams with v4 pro. When will ds or another lab release a fixed engram model? Fixed engrams will be the

Agents

Where agent evals are going: Agent-as-a-Judge

Agents changed what failure looks like, and the evaluation layer has to change with them. Why agent-as-a-judge is moving from research paper to production eval stack. The post Where agent evals are go

agentsarize-ai

WIP: LLM Odyssey: A Game-Based Platform for Teaching LLM Engineering Concepts

arXiv:2608.16924v1 Announce Type: cross Abstract: This work-in-progress (WIP) innovative practice category paper presents LLM Odyssey, an open source, browser-based serious gaming platform comprising

applicationsarxiv-cs-ai

A Unified Mamba--MoE Surrogate for Closed-Loop Simulation and Measurement-Window Forecasting of Inverter Transients

arXiv:2608.15051v1 Announce Type: new Abstract: This paper proposes a Mamba surrogate model with mixture-of-experts (MoE) routing to represent the transient dynamics of inverter-based resources. A Mam

Admissibility-Preserving Control for Strict-Feedback Nonlinear Systems with Asymmetric Actuator Constraints

arXiv:2608.15375v1 Announce Type: cross Abstract: This paper develops Admissibility-Preserving Control (APC), a realization-centered safety-critical control framework for strict-feedback systems subje

An Empirical Study of Training Pixel-Space Text-to-Image Diffusion Models

arXiv:2608.16887v1 Announce Type: new Abstract: This paper investigates an increasingly important topic in generative modeling: pixel-space diffusion models. Although numerous studies have explored th

researcharxiv-cs-cv

Auxiliary uncertainty signals for LLM-assisted systematic review screening: a benchmark across eight Cohen drug-class reviews

model-releasesarxiv-cs-cl

arXiv:2608.14551v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for title-abstract screening in systematic reviews, but their decisions lack calibrated uncertainty.

Calibration-Free Vehicle Speed Estimation: A Monocular Keypoint-Template Approach

arXiv:2608.16785v1 Announce Type: new Abstract: This paper proposes a calibration-free framework for reliably and effectively estimating vehicle speeds from monocular videos, without relying on roadwa

safetyarxiv-cs-cv

Chronocooked: A Benchmark for Implicit Interval Timing in Reinforcement Learning Agents

arXiv:2608.16666v1 Announce Type: new Abstract: This paper presents Chronocooked, a reinforcement learning (RL) benchmark suite for studying implicit interval timing in RL agents. Inspired by Overcook

Computational KJ-Ho: An Analyst-Bias-Free Insight Extraction Framework from Large-Scale Qualitative Data Using Domain-Specialized LLMs

arXiv:2608.16467v1 Announce Type: cross Abstract: The qualitative research methodologies that underpin consumer-insight generation - the KJ method, Grounded Theory, and Thematic Analysis - share a str

safetyarxiv-cs-cl

CoupVisor: Strategy Optimization by Round and Challenge Decision Support

arXiv:2608.15868v1 Announce Type: new Abstract: This paper presents CoupVisor, a decision-support system for the hidden-information card game Coup. It addresses two questions: what a player should do

safetyarxiv-cs-ai

Demand-Driven Vertiport Siting and Discrete-Event Fleet Simulation for On-Demand Urban Air Mobility Network Design

arXiv:2608.14974v1 Announce Type: new Abstract: This paper presents a demand-driven framework for on-demand Urban Air Mobility (UAM) network design that links vertiport siting, fleet simulation, and d

applicationsarxiv-cs-ai

DirMixE: Harnessing Test Agnostic Long-tail Recognition with Hierarchical Label Variations

arXiv:2405.07780v3 Announce Type: replace-cross Abstract: This paper explores test-agnostic long-tail recognition, a challenging long-tail task where the test label distributions are unknown and arbit

Disentangling Pictorial Cue Understanding from Language Bias in VLMs via Depth Ordering Task

model-releasesarxiv-cs-cv

arXiv:2607.01503v2 Announce Type: replace Abstract: In this paper, we study depth perception of vision-language models (VLMs) to isolate the effects of pictorial depth cues and disentangle vision and

DumpsterCluster: From Dumpster Diving to Serving LLaMA-70B on $60 GPUs

arXiv:2608.14614v1 Announce Type: cross Abstract: As AI datacenters retire functional GPUs, vast quantities of still capable accelerators enter secondary markets. This paper investigates whether these

Dynamic Evidence Collection Ecosystem for Assessment Integrity and Authentic Competence

arXiv:2608.16016v1 Announce Type: cross Abstract: Generative Artificial Intelligence (GenAI) can produce high-quality essays, code, and design artefacts, challenging the validity of conventional asses

Evidence of conceptual mastery in the application of rules by Large Language Models

arXiv:2503.00992v2 Announce Type: replace Abstract: In this paper we leverage psychological methods to investigate LLMs' conceptual mastery in applying rules. We introduce a novel procedure to match t

From Doyle to AGM: A Survey and an Implementation Roadmap for Belief Change

arXiv:2608.14567v1 Announce Type: new Abstract: This paper presents a targeted narrative review establishing the historical and theoretical foundations for computational belief change implementation.

From Generation to Matching: A Development Report on Personalized Chinese Handwriting

arXiv:2608.15812v1 Announce Type: new Abstract: This paper documents a frozen engineering project on personalized Chinese handwriting. The project started from approximately 200 real handwriting image

researcharxiv-cs-cv

From Monte Carlo to neural networks approximations of boundary value problems

arXiv:2209.01432v4 Announce Type: replace-cross Abstract: In this paper we study probabilistic and neural network approximations for solutions to Poisson equation subject to Holder data in general bou

Generated Context versus Governed State: Functional Conditions for Accountable Longitudinal Clinical Reasoning

arXiv:2608.14804v1 Announce Type: new Abstract: Large language models (LLMs) have become the dominant interface of clinical artificial intelligence, yet the interface they expose (text in, text out, o

GUIDER: Evaluating Goal-Free Human Intent Inference for Teleoperated Manipulation on Real-Robot Data

arXiv:2608.15446v1 Announce Type: new Abstract: This paper presents an evaluation of a goal-free probabilistic framework for human intent inference during robotic manipulation. We deploy the Global Us

applicationsarxiv-cs-ro

Macroeconomic Forecasting with Large Language Models

arXiv:2407.00890v5 Announce Type: replace-cross Abstract: This paper presents a comparative analysis evaluating the accuracy of Large Language Models (LLMs) against traditional macro time series forec

applicationsarxiv-cs-cl

Marker-Constrained Pose-Graph Correction for Cross-Platform Georeferencing in GNSS-Denied Environments

arXiv:2608.16281v1 Announce Type: new Abstract: Autonomous operation in GNSS-denied environments requires heterogeneous mapping pipelines to maintain a consistent spatial reference. This paper present

One-shot Robust Federated Learning of Independent Component Analysis

arXiv:2505.20532v2 Announce Type: replace Abstract: This paper studies robust one-shot aggregation for distributed and federated Independent Component Analysis (ICA). In this setting, each client comp

Personalized Auto-Research: Towards a True AI Co-Scientist

arXiv:2608.14881v1 Announce Type: new Abstract: AI co-scientists that generate hypotheses, retrieve related work, design experiments, execute code, and draft full papers are beginning to change how re

Reasoning-supported Robustness Validation of Automotive E/E Components

arXiv:2608.16421v1 Announce Type: new Abstract: This paper presents an ontology-supported approach to tackle the complexity of the Robustness Validation (RV) process of automotive electrical/electroni

Rethinking Token-wise Feature Caching: Accelerating Diffusion Transformers with Dual Feature Caching

arXiv:2412.18911v3 Announce Type: replace-cross Abstract: Diffusion Transformers (DiT) have become the dominant methods in image and video generation yet still suffer substantial computational costs.

Retrieval-guided Twin Fusion with Similarity-aware Contrast for Molecule-Text Alignment

model-releasesarxiv-cs-lg

arXiv:2608.16005v1 Announce Type: new Abstract: This paper studies the problem of molecule-text alignment, which aims to project molecules and their textual descriptions into a joint latent space for

Seeing the Bigger Picture: 3D Latent Mapping for Mobile Manipulation Policy Learning

arXiv:2510.03885v4 Announce Type: replace Abstract: In this paper, we demonstrate that mobile manipulation policies utilizing a 3D latent map achieve stronger spatial and temporal reasoning than polic

Self-Bootstrapping Automated Program Repair: Using LLMs to Generate and Evaluate Synthetic Training Data for Bug Repair

arXiv:2505.07372v3 Announce Type: replace-cross Abstract: This paper presents a novel methodology for enhancing Automated Program Repair (APR) through synthetic data generation utilizing Large Languag

Shape Operator PCA: Curvature-Aware Projections for Geometric Machine Learning

arXiv:2608.15313v1 Announce Type: cross Abstract: In this paper, we propose SHOPCA (Shape Operator-based Principal Component Analysis), a novel method for unsupervised metric learning and dimensionali

Structuring Semantic Embeddings for Principle Evaluation: A Prototype-Guided Contrastive Learning Approach

arXiv:2608.15224v1 Announce Type: new Abstract: Reliable post-hoc evaluation asks whether already generated text satisfies a target criterion after generation. In this paper we study a focused frozen-

The First ChineseBabyLM Challenge: training data-efficient and cognitively plausible language models for Chinese

model-releasesarxiv-cs-cl

arXiv:2607.10745v2 Announce Type: replace Abstract: This paper presents the first ChineseBabyLM Challenge, organized as part of NLPCC 2026. The challenge asked participants to train language models fr