Search: “routing”

arXiv:2604.20817v1 Announce Type: cross Abstract: Language models trained on natural text learn to represent numbers using periodic features with dominant periods at T=2, 5, 10. In this paper, we iden

tutorialsarxiv-cs-ai

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Device-Native Autonomous Agents for Privacy-Preserving Negotiations

DGX agent

arXiv:2601.00911v3 Announce Type: replace-cross Abstract: Automated negotiations in insurance and business-to-business (B2B) commerce encounter substantial challenges. Current systems force a trade-of

local-aiarxiv-cs-ai

23 Apr 2026

Do Small Language Models Know When They're Wrong? Confidence-Based Cascade Scoring for Educational Assessment

arXiv:2604.19781v1 Announce Type: cross Abstract: Automated scoring of student work at scale requires balancing accuracy against cost and latency. In 'cascade' systems, small language models (LMs) han

Do We Need Bigger Models for Science? Task-Aware Retrieval with Small Language Models

arXiv:2604.01965v2 Announce Type: replace-cross Abstract: Scientific knowledge discovery increasingly relies on large language models, yet many existing scholarly assistants depend on proprietary syst

Fourier Series Coder: A Novel Perspective on Angle Boundary Discontinuity Problem for Oriented Object Detection

arXiv:2604.20281v1 Announce Type: new Abstract: With the rapid advancement of intelligent driving and remote sensing, oriented object detection has gained widespread attention. However, achieving high

Handbook of Rough Set Extensions and Uncertainty Models

arXiv:2604.19794v1 Announce Type: new Abstract: Rough set theory models uncertainty by approximating target concepts through lower and upper sets induced by indiscernibility, or more generally, by gra

Agents

HaS: Accelerating RAG through Homology-Aware Speculative Retrieval

arXiv:2604.20452v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) expands the knowledge boundary of large language models (LLMs) at inference by retrieving external documents as c

agentsarxiv-cs-cl

Agents

Neural Bandit Based Optimal LLM Selection for a Pipeline of Subtasks

arXiv:2508.09958v3 Announce Type: replace Abstract: As large language models (LLMs) become increasingly popular, there is a growing need to predict which out of a set of LLMs will yield a successful a

agentsarxiv-cs-cl

Opportunistic Bone-Loss Screening from Routine Knee Radiographs Using a Multi-Task Deep Learning Framework with Sensitivity-Constrained Threshold Optimization

arXiv:2604.20268v1 Announce Type: new Abstract: Background: Osteoporosis and osteopenia are often undiagnosed until fragility fractures occur. Dual-energy X-ray absorptiometry (DXA) is the reference s

Physics-Informed Conditional Diffusion for Motion-Robust Retinal Temporal Laser Speckle Contrast Imaging

arXiv:2604.20594v1 Announce Type: new Abstract: Retinal laser speckle contrast imaging (LSCI) is a noninvasive optical modality for monitoring retinal blood flow dynamics. However, conventional tempor

Pre-Execution Query Slot-Time Prediction in Cloud Data Warehouses: A Feature-Scoped Machine Learning Approach

arXiv:2604.20145v1 Announce Type: cross Abstract: Cloud data warehouses bill compute based on slot-time consumed. In shared multi-tenant environments, query cost is highly variable and hard to estimat

Skyline-First Traversal as a Control Mechanism for Multi-Criteria Graph Search

arXiv:2604.19807v1 Announce Type: new Abstract: In multi-criteria graph traversal, paths are compared via Pareto dominance, an ordering that identifies which paths are non-dominated, but says nothing

TactileEval: A Step Towards Automated Fine-Grained Evaluation and Editing of Tactile Graphics

arXiv:2604.19829v1 Announce Type: new Abstract: Tactile graphics require careful expert validation before reaching blind and visually impaired (BVI) learners, yet existing datasets provide only coarse

The OpenHands Software Agent SDK: A Composable and Extensible Foundation for Production Agents

arXiv:2511.03690v2 Announce Type: replace-cross Abstract: Agents are now used widely in the process of software development, but building production-ready software engineering agents is a complex task

WorkflowGen:an adaptive workflow generation mechanism driven by trajectory experience

arXiv:2604.19756v1 Announce Type: cross Abstract: Large language model (LLM) agents often suffer from high reasoning overhead, excessive token consumption, unstable execution, and inability to reuse p

X-IONet: Cross-Platform Inertial Odometry Network for Pedestrian and Legged Robot

arXiv:2511.08277v2 Announce Type: replace-cross Abstract: Learning-based inertial odometry has achieved remarkable progress in pedestrian navigation. However, extending these methods to quadruped robo

A PPA-Driven 3D-IC Partitioning Selection Framework with Surrogate Models

arXiv:2604.18806v1 Announce Type: new Abstract: 3D-IC netlist partitioning is commonly optimized using proxy objectives, while final PPA is treated as a costly evaluation rather than an optimization s

Accelerating trajectory optimization with Sobolev-trained diffusion policies

arXiv:2604.19011v1 Announce Type: new Abstract: Trajectory Optimization (TO) solvers exploit known system dynamics to compute locally optimal trajectories through iterative improvements. A downside is

local-aiarxiv-cs-lg

CAHAL: Clinically Applicable resolution enHAncement for Low-resolution MRI scans

arXiv:2604.18781v1 Announce Type: new Abstract: Large-scale automated morphometric analysis of brain MRI is limited by the thick-slice, anisotropic acquisitions prevalent in routine clinical practice.

safetyarxiv-cs-cv

Council Mode: Mitigating Hallucination and Bias in LLMs via Multi-Agent Consensus

arXiv:2604.02923v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs), particularly those employing Mixture-of-Experts (MoE) architectures, have achieved remarkable capabilities acros

Diagnosable ColBERT: Debugging Late-Interaction Retrieval Models Using a Learned Latent Space as Reference

arXiv:2604.19566v1 Announce Type: cross Abstract: Reliable biomedical and clinical retrieval requires more than strong ranking performance: it requires a practical way to find systematic model failure

Diamond Maps: Efficient Reward Alignment via Stochastic Flow Maps

arXiv:2602.05993v2 Announce Type: replace-cross Abstract: Flow and diffusion models produce high-quality samples, but adapting them to user preferences or constraints post-training remains costly and

safetyarxiv-cs-ai

Evaluation-driven Scaling for Scientific Discovery

arXiv:2604.19341v1 Announce Type: cross Abstract: Language models are increasingly used in scientific discovery to generate hypotheses, propose candidate solutions, implement systems, and iteratively

local-aiarxiv-cs-ai

HardNet++: Nonlinear Constraint Enforcement in Neural Networks

arXiv:2604.19669v1 Announce Type: new Abstract: Enforcing constraint satisfaction in neural network outputs is critical for safety, reliability, and physical fidelity in many control and decision-maki

local-aiarxiv-cs-lg

Mixture of Predefined Experts: Maximizing Data Usage on Vertical Federated Learning

arXiv:2602.12708v2 Announce Type: replace Abstract: Vertical Federated Learning (VFL) has emerged as a critical paradigm for collaborative model training in privacy-sensitive domains such as finance a

safetyarxiv-cs-lg

Probing for Reading Times

arXiv:2604.18712v1 Announce Type: new Abstract: Probing has shown that language model representations encode rich linguistic information, but it remains unclear whether they also capture cognitive sig

Scalable Memristive-Friendly Reservoir Computing for Time Series Classification

arXiv:2604.19343v1 Announce Type: cross Abstract: Memristive devices present a promising foundation for next-generation information processing by combining memory and computation within a single physi

Stable-RAG: Mitigating Retrieval-Permutation-Induced Hallucinations in Retrieval-Augmented Generation

arXiv:2601.02993v4 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) has become a key paradigm for reducing factual hallucinations in Large Language Models (LLMs), yet little is kn

Tutorials

Thinking Before Matching: A Reinforcement Reasoning Paradigm Towards General Person Re-Identification

arXiv:2604.19218v1 Announce Type: new Abstract: Learning identity-discriminative representations with multi-scene generality has become a critical objective in person re-identification (ReID). However

tutorialsarxiv-cs-cv

Towards Generalization of Graph Neural Networks for AC Optimal Power Flow

arXiv:2510.06860v2 Announce Type: replace-cross Abstract: AC Optimal Power Flow (ACOPF) is computationally intensive for large-scale grids, often requiring prohibitive solution times with conventional

Adaptive Forensic Feature Refinement via Intrinsic Importance Perception

arXiv:2604.16879v1 Announce Type: new Abstract: With the rapid development of generative models and multimodal content editing technologies, the key challenge faced by synthetic image detection (SID)

Align Documents to Questions: Question-Oriented Document Rewriting for Retrieval-Augmented Generation

arXiv:2604.17325v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) enhances the factuality of Large Language Models (LLMs) by incorporating retrieved documents and/or generated conte

Aligning Backchannel and Dialogue Context Representations via Contrastive LLM Fine-Tuning

arXiv:2604.16622v1 Announce Type: new Abstract: Backchannels (e.g., `yeah', `mhm', and `right') are short, non-interruptive feedback signals whose lexical form and prosody jointly convey pragmatic mea

Beyond Overlap Metrics: Rewarding Reasoning and Preferences for Faithful Multi-Role Dialogue Summarization

arXiv:2604.17188v1 Announce Type: new Abstract: Multi-role dialogue summarization requires modeling complex interactions among multiple speakers while preserving role-specific information and factual

Bilinear Input Modulation for Mamba: Koopman Bilinear Forms for Memory Retention and Multiplicative Computation

arXiv:2604.17221v1 Announce Type: cross Abstract: Selective State Space Models (SSMs), notably Mamba, employ diagonal state transitions that limit both memory retention and bilinear computational capa

EasyVideoR1: Easier RL for Video Understanding

arXiv:2604.16893v1 Announce Type: new Abstract: Reinforcement learning from verifiable rewards (RLVR) has demonstrated remarkable effectiveness in improving the reasoning capabilities of large languag

End-to-end Listen, Look, Speak and Act

model-releasesarxiv-cs-cl

arXiv:2510.16756v2 Announce Type: replace-cross Abstract: Human interaction is inherently multimodal and full-duplex: we listen while watching, speak while acting, and fluidly adapt to turn-taking and

Heterogeneous Self-Play for Realistic Highway Traffic Simulation

arXiv:2604.16406v1 Announce Type: cross Abstract: Realistic highway simulation is critical for scalable safety evaluation of autonomous vehicles, particularly for interactions that are too rare to stu

safetyarxiv-cs-lg

ICLAD: In-Context Learning with Comparison-Guidance for Audio Deepfake Detection

arXiv:2604.16749v1 Announce Type: cross Abstract: Audio deepfakes pose a significant security threat, yet current state-of-the-art (SOTA) detection systems do not generalize well to realistic in-the-w

researcharxiv-cs-cl

MHSafeEval: Role-Aware Interaction-Level Evaluation of Mental Health Safety in Large Language Models

arXiv:2604.17730v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly explored as scalable tools for mental health counseling, yet evaluating their safety remains challenging d

Missing Pattern Tree based Decision Grouping and Ensemble for Enhancing Pair Utilization in Deep Incomplete Multi-View Clustering

arXiv:2512.21510v2 Announce Type: replace-cross Abstract: Real-world multi-view data often exhibit highly inconsistent missing patterns, posing significant challenges for incomplete multi-view cluster

Applications

MoGERNN: An Inductive Traffic Predictor for Unobserved Locations

arXiv:2501.12281v2 Announce Type: replace Abstract: Given a partially observed road network, how can we predict the traffic state of interested unobserved locations? Traffic prediction is crucial for

applicationsarxiv-cs-lg

Motif-Video 2B: Technical Report

arXiv:2604.16503v1 Announce Type: new Abstract: Training strong video generation models usually requires massive datasets, large parameter counts, and substantial compute. In this work, we ask whether

OD3: Optimization-free Dataset Distillation for Object Detection

arXiv:2506.01942v2 Announce Type: replace Abstract: Training large neural networks on large-scale datasets requires substantial computational resources, particularly for dense prediction tasks such as

Agents

OneVL: One-Step Latent Reasoning and Planning with Vision-Language Explanation

arXiv:2604.18486v1 Announce Type: cross Abstract: Chain-of-Thought (CoT) reasoning has become a powerful driver of trajectory prediction in VLA-based autonomous driving, yet its autoregressive nature

agentsarxiv-cs-cl

PlanViz: Evaluating Planning-Oriented Image Generation and Editing for Computer-Use Tasks

arXiv:2602.06663v2 Announce Type: replace Abstract: Unified multimodal models (UMMs) have shown impressive capabilities in generating natural images and supporting multimodal reasoning. However, their

Privacy-R1: Privacy-Aware Multi-LLM Agent Collaboration via Reinforcement Learning

arXiv:2510.16054v2 Announce Type: replace-cross Abstract: When users submit queries to Large Language Models (LLMs), their prompts can often contain sensitive data, forcing a difficult choice: Send th

local-aiarxiv-cs-cl

Retrieval-Augmented Multimodal Model for Fake News Detection

arXiv:2604.18112v1 Announce Type: new Abstract: In recent years, multimodal multidomain fake news detection has garnered increasing attention. Nevertheless, this direction presents two significant cha