Search: “papers”

Wild3R: Feed-Forward 3D Gaussian Splatting from Unconstrained Sparse Photo Collection

arXiv:2606.11894v1 Announce Type: new Abstract: Feed-forward 3D Gaussian Splatting (3DGS) removes the need for time-consuming per-scene optimization required by traditional 3DGS. However, existing fee

applicationsarxiv-cs-cv

11 Jun 2026

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XPR: An Extensible Cross-Platform Point-Based Differentiable Renderer

DGX agent

arXiv:2606.11529v1 Announce Type: cross Abstract: Point-based differentiable rendering underpins modern 3D reconstruction, novel-view synthesis, and learning-based graphics pipelines, but developing n

researcharxiv-cs-cv

11 Jun 2026

5% > 100%: Flatness Preference is All You Need for Multimodal Parameter-Efficient Fine-Tuning

model-releasesarxiv-cs-cv

arXiv:2606.10488v1 Announce Type: new Abstract: Parameter-Efficient Fine-Tuning (PEFT) methods provide a streamlined and efficient tool for adapting large models to domain-specific multimodal downstre

A Comprehensive Survey of Direct Preference Optimization: Datasets, Theories, Variants, and Applications

arXiv:2410.15595v4 Announce Type: replace Abstract: With the rapid advancement of large language models (LLMs), aligning policy models with human preferences has become increasingly critical. Direct P

A Continuous-Time Markov Chain Framework for Insertion Language Models

arXiv:2606.10199v1 Announce Type: cross Abstract: Insertion Language Models (ILMs) offer several advantages over left-to-right generation and mask-based generation. However, existing formulations of i

researcharxiv-cs-cl

A Distributed Multi-UGV Exploration Framework With Loop-Aware Planning and Descriptor-Aided Localization in Resource-Limited Environments

arXiv:2606.11088v1 Announce Type: new Abstract: Robust and efficient cooperative exploration with multiple unmanned ground vehicles (UGVs) in unknown, GPSdenied, and bandwidth-limited environments wit

agentsarxiv-cs-ro

A Machine Learning Theory Perspective on Strategic Litigation

arXiv:2506.03411v2 Announce Type: replace Abstract: Strategic litigation involves bringing a case to court with the goal of having an impact beyond resolving the particular dispute at hand. In a commo

applicationsarxiv-cs-lg

A Unified Multi-Modal Framework for Intelligent Financial Systems: Integrating Reinforcement Learning, High-Frequency Trading, and Game-Theoretic Approaches with Cross-Modal Sentiment Analysis

arXiv:2606.10412v1 Announce Type: new Abstract: The rapid evolution of financial technology demands sophisticated artificial intelligence systems capable of handling diverse challenges across multiple

Accelerating NeurASP with vectorization and caching

arXiv:2606.10787v1 Announce Type: new Abstract: Neurosymbolic AI combines neural networks with symbolic programs to create robust and explainable predictions. One such framework is NeurASP, which trai

AdaGC: Enhancing LLM Pretraining Stability via Adaptive Gradient Clipping

model-releasesarxiv-cs-lg

arXiv:2502.11034v3 Announce Type: replace Abstract: Loss spikes remain a persistent obstacle in large-scale language model pretraining. While previous research has attempted to identify the root cause

Agentic Social Affordance Framework (ASAF): Agent Identity Design as a Collaboration Interface in Multi-Agent Systems

arXiv:2606.09832v1 Announce Type: cross Abstract: As AI systems evolve from single conversational agents to complex multi-agent architectures, a critical design dimension has been overlooked: how the

AgenticNav: Zero-Shot Vision-and-Language Navigation as a Tool-Calling Harness

model-releasesarxiv-cs-ro

arXiv:2606.10577v1 Announce Type: new Abstract: Zero-shot vision-and-language navigation in continuous environments (VLN-CE) has recently become feasible with large vision-language models (VLMs). Howe

AgniNav: Configuration-Driven Cross-Embodiment Local Planning for Robot Navigation

model-releasesarxiv-cs-ro

arXiv:2606.10903v1 Announce Type: new Abstract: Monocular local navigation is attractive for lightweight robots, but existing vision-based policies often couple perception to a specific body, camera h

AI-Driven Analytics of Team-Teaching Talk: Acoustic Patterns across Experience, Cohorts and the Learning Design

arXiv:2606.09831v1 Announce Type: cross Abstract: As classroom cohorts expand, team teaching is increasingly used to integrate the expertise and pedagogical perspectives of multiple teachers. Yet, the

Algorithmic and Minimax Complexities in Kernel Bandits

arXiv:2606.11171v1 Announce Type: new Abstract: Gaussian-process upper confidence bound (GP-UCB) and decision-estimation-coefficient (DEC) methods may appear, at first sight, to belong to different th

An (epsilon,elta)-accurate level set estimation with a stopping criterion

arXiv:2503.20272v2 Announce Type: replace-cross Abstract: The level set estimation problem seeks to identify regions within a set of candidate points where an unknown and costly to evaluate function's

An Exposure-Time-Aligned Primary-Path Architecture for Autonomous-Driving ECUs

arXiv:2606.10856v1 Announce Type: new Abstract: While end-to-end (E2E) autonomous driving has become the dominant research direction, production vehicles continue to rely on modular multi-NN pipelines

agentsarxiv-cs-ro

AnimaSpark: A Feed-Forward Method for Animating Arbitrary 3D Objects

arXiv:2606.10988v1 Announce Type: new Abstract: While recent advancements in generative AI have substantially accelerated static 3D model creation workflows, the synthesis of category-agnostic 3D anim

safetyarxiv-cs-cv

Atomic Intent Reasoning: Bringing LLM Semantics to Industrial Cross-Domain Recommendations

arXiv:2606.10357v1 Announce Type: cross Abstract: Cross-domain recommendation is a core problem in content-to-e-commerce platforms. Its objective is to leverage user interactions with content to infer

applicationsarxiv-cs-ai

Automated Alignment between Elicitation Interviews and Requirements

arXiv:2510.08622v2 Announce Type: replace Abstract: Software requirements are derived from a variety of elicitation techniques, many of which have a conversational nature, like interviews. However, ev

safetyarxiv-cs-cl

Automated Pronunciation Evaluation for Korean Toddler Speech using Speech Diarization and Self-Supervised Learning

arXiv:2606.10213v1 Announce Type: cross Abstract: Speech sound disorders affect approximately 44% of Korean pediatric communication disorder cases, yet automated assessment tools for Korean toddler sp

Business World Model

arXiv:2606.10044v1 Announce Type: new Abstract: Businesses are increasingly adopting AI-enabled tools to improve productivity, reduce costs, and enhance products and services. However, the transformat

Bypassing Copyright Protection in Diffusion-based Customization via Two-Stage Latent Feature Optimization

arXiv:2606.09909v1 Announce Type: cross Abstract: With the growing concerns over copyright infringement in diffusion-based customization, adversarial attacks have emerged as a prominent defense strate

Can Multi-Agent LLMs Identify Their Peers? Stylometric Fingerprinting in Role-Constrained Political Analysis

model-releasesarxiv-cs-ai

arXiv:2606.09854v1 Announce Type: cross Abstract: Multi-agent large language model (LLM) pipelines for political statement analysis are vulnerable to peer-preservation bias: models tend to protect pee

ClinReadNet: A clinical reading-inspired network for low-dose abdominal CT image quality assessment

arXiv:2606.10372v1 Announce Type: new Abstract: In abdominal CT imaging, developing a low-dose, no-reference image quality assessment (No-reference IQA) model that mimics doctors' reading habits for e

researcharxiv-cs-cv

CommonLID: Re-evaluating State-of-the-Art Language Identification Performance on Web Data

model-releasesarxiv-cs-cl

arXiv:2601.18026v2 Announce Type: replace Abstract: Language identification (LID) is a fundamental step in curating multilingual corpora. However, LID models still perform poorly for many languages, e

Compiling Rewrite Rules to Finite-State Transducers with the Worsening Trick

arXiv:2606.10059v1 Announce Type: cross Abstract: Finite-state transducers (FSTs) are essential for modeling string rewriting in computational linguistics and natural language processing (NLP), partic

applicationsarxiv-cs-cl

Tutorials

Content-Induced Spatial-Spectral Aggregation Network for Change Detection in Remote Sensing Images

arXiv:2606.10328v1 Announce Type: cross Abstract: The integration of spatial and spectral information is beneficial to the improvement of change detection performance. However, existing methods cannot

tutorialsarxiv-cs-ai

Convergence of Monte Carlo Optimistic Policy Iteration: Beyond Uniform State-Action Updates

arXiv:2606.10580v1 Announce Type: cross Abstract: The asymptotic behaviour of Monte Carlo optimistic policy iteration (MC-O-PI) is a long-standing open question. When the model of the environment is u

CoTAL: Human-in-the-Loop Prompt Engineering for Generalizable Formative Assessment Scoring and Feedback

model-releasesarxiv-cs-cl

arXiv:2504.02323v4 Announce Type: replace Abstract: Large language models (LLMs) have created new opportunities to assist teachers and support student learning. While researchers have explored various

Culturally-Aware AI for Cross-Boundary Community Learning: Undergraduate Innovation at the Intersection of Computation and Design

arXiv:2606.09041v1 Announce Type: cross Abstract: Research on artificial intelligence in education (AIED) is rapidly expanding, yet technical progress often lacks human-centered grounding and adequate

applicationsarxiv-cs-ai

Decision-Calibrated Conformal Uncertainty for Pacing Decisions in Streaming Advertising

arXiv:2606.10187v1 Announce Type: cross Abstract: We develop a decision-calibrated conformal framework for pacing decisions in streaming advertising. Pacing depends on uncertain future inventory, dema

safetyarxiv-cs-lg

Deeper or Wider: A Perspective from Optimal Generalization Error with Sobolev Loss

arXiv:2402.00152v5 Announce Type: replace Abstract: Constructing the architecture of a neural network is a challenging pursuit for the machine learning community, and the dilemma of whether to go deep

Disjoint or Overlapping? Inference Windowing for Reconstruction-Based Time Series Anomaly Detection

model-releasesarxiv-cs-lg

arXiv:2606.09874v1 Announce Type: new Abstract: Reconstruction-based methods are widely used for time series anomaly detection, where models are trained to reconstruct subsequences, and anomalies are

Dmsh: A Multi-Agent Reinforcement Learning Framework for All-Quad Mesh Generation

arXiv:2606.10601v1 Announce Type: cross Abstract: Generating high-quality meshes for arbitrary geometries remains a fundamental bottleneck in computational engineering, often demanding heuristic tunin

Do LLMsMakeNeural Distinguishers Wise?

arXiv:2606.10692v1 Announce Type: cross Abstract: Neural distinguishers are a cryptanalysis method for symmetric-key cryptography that trains machine learning models on pairs of plaintexts and ciphert

Duality for Optimal Multi-Item, Multi-Bidder Auction Design: Revenue Certificates through Deep Learning

arXiv:2606.10112v1 Announce Type: cross Abstract: Characterizing revenue-optimal auctions for multi-item, multi-bidder settings remains a fundamental open problem, with no known closed-form solution e

Dynamics of Adversarial Attacks on Large Language Model-Based Search Engines

arXiv:2501.00745v3 Announce Type: replace-cross Abstract: The increasing integration of Large Language Model (LLM) based search engines has transformed the landscape of information retrieval. However,

Enabling Progressive Whole-slide Image Analysis with Multi-scale Pyramidal Network

model-releasesarxiv-cs-cv

arXiv:2602.01951v2 Announce Type: replace Abstract: Multiple-instance Learning (MIL) is commonly used for computational pathology (CPath), where multi-scale features are essential for capturing both f

FoA-SR: Faithful or Aesthetic? Profile-Aware Preference Optimization for Real-World Image Super-Resolution

arXiv:2606.10275v1 Announce Type: new Abstract: Real-world image super-resolution (SR) is often designed with a single restoration objective, despite the current capacity of generative models to produ

applicationsarxiv-cs-cv

FSS-Net: Frequency-Spatial Synergy Network with Wavelet Attention for Carotid Artery Ultrasound Segmentation

arXiv:2606.10378v1 Announce Type: new Abstract: Accurate segmentation of carotid arteries in ultrasound imaging is critical for stroke risk assessment. However, speckle noise, low contrast, and blurre

researcharxiv-cs-cv

Gaming AI-Assisted Peer Reviews Poses New Risks to the Scientific Community

model-releasesarxiv-cs-ai

arXiv:2606.10159v1 Announce Type: cross Abstract: AI is increasingly used to support scientific peer review, from manuscript screening, reviewer assistance to editorial triage. Although such systems p

Generative Explainability for Next-Generation Networks: LLM-Augmented XAI with Mutual Feature Interactions

arXiv:2606.10942v1 Announce Type: cross Abstract: As artificial intelligence and machine learning (AI/ML) models become integral to network operations, their lack of transparency poses a significant b

Geometrically Averaged Hard Target Updates for Linear Q-Learning

arXiv:2606.10835v1 Announce Type: cross Abstract: Periodic hard target updates are among the most common stabilization devices in modern deep Q-learning. Recent studies suggest that target updates can

Geometry-Aware Reinforcement Learning for 2D Irregular Nesting

model-releasesarxiv-cs-cv

arXiv:2606.10611v1 Announce Type: cross Abstract: Traditional heuristic solvers for the 2D irregular nesting problem share a fundamental limitation: they are blind to polygon geometry, relying on guid

Gradient based Bilevel for Inverse Optimal Control, a Riemannian approach

arXiv:2606.10841v1 Announce Type: new Abstract: Inverse Optimal Control (IOC) aims to recover the cost function that explains observed trajectories as solutions of an optimal control problem. Classica

researcharxiv-cs-ro

Harnessing the Collective Intelligence of AI Agents in the Wild for New Discoveries

arXiv:2606.10402v1 Announce Type: cross Abstract: Scientific discovery is often a collective process: researchers share partial results, inspect failed attempts, and build on each other's ideas over l

Hasse Diagrams for Attention: A Partial Order Framework for Designing Transformer Masks

arXiv:2606.09951v1 Announce Type: new Abstract: During the training of large Transformer models, attention masks regulate the scope and direction of information flow across a sequence. Numerous mask v