Search: “routing”

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

22 Apr 2026

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Tutorials

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

DGX agent

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

22 Apr 2026

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

researcharxiv-cs-ai

22 Apr 2026

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

researcharxiv-cs-lg

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

researcharxiv-cs-cv

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

Rewind-IL: Online Failure Detection and State Respawning for Imitation Learning

arXiv:2604.16683v1 Announce Type: cross Abstract: Imitation learning has enabled robots to acquire complex visuomotor manipulation skills from demonstrations, but deployment failures remain a major ob

local-aiarxiv-cs-cv

RoTRAG: Rule of Thumb Reasoning for Conversation Harm Detection with Retrieval-Augmented Generation

model-releasesarxiv-cs-cl

arXiv:2604.17301v1 Announce Type: new Abstract: Detecting harmful content in multi turn dialogue requires reasoning over the full conversational context rather than isolated utterances. However, most

SaFeR-Steer: Evolving Multi-Turn MLLMs via Synthetic Bootstrapping and Feedback Dynamics

arXiv:2604.16358v1 Announce Type: cross Abstract: MLLMs are increasingly deployed in multi-turn settings, where attackers can escalate unsafe intent through the evolving visual-text history and exploi

SemLT3D: Semantic-Guided Expert Distillation for Camera-only Long-Tailed 3D Object Detection

arXiv:2604.18476v1 Announce Type: new Abstract: Camera-only 3D object detection has emerged as a cost-effective and scalable alternative to LiDAR for autonomous driving, yet existing methods primarily

safetyarxiv-cs-cv

Sessa: Selective State Space Attention

arXiv:2604.18580v1 Announce Type: cross Abstract: Modern sequence models are dominated by Transformers, where self-attention mixes information from the visible context in an input-dependent way. Howev

researcharxiv-cs-cl

Subject-Aware Multi-Granularity Alignment for Zero-Shot EEG-to-Image Retrieval

arXiv:2604.17782v1 Announce Type: new Abstract: Zero-shot EEG-to-image retrieval aims to decode perceived visual content from electroencephalography (EEG) by aligning neural responses with pretrained

The Provenance Gap in Clinical AI: Evidence-Traceable Temporal Knowledge Graphs for Rare Disease Reasoning

arXiv:2604.17114v1 Announce Type: new Abstract: Frontier large language models generate clinically accurate outputs, but their citations are often fabricated. We term this the Provenance Gap. We teste

TMD-TTS: A Unified Tibetan Multi-Dialect Text-to-Speech Framework for U-Tsang, Amdo and Kham Speech Dataset Generation

arXiv:2509.18060v2 Announce Type: replace Abstract: Tibetan is a low-resource language with limited parallel speech corpora spanning its three major dialects (U-Tsang, Amdo, and Kham), limiting progre

researcharxiv-cs-cl

Train Separately, Merge Together: Modular Post-Training with Mixture-of-Experts

arXiv:2604.18473v1 Announce Type: new Abstract: Extending a fully post-trained language model with new domain capabilities is fundamentally limited by monolithic training paradigms: retraining from sc

safetyarxiv-cs-lg

Transition-Matrix Regularization for Next Dialogue Act Prediction in Counselling Conversations

arXiv:2604.18539v1 Announce Type: new Abstract: This paper studies how empirical dialogue-flow statistics can be incorporated into Next Dialogue Act Prediction (NDAP). A KL regularization term is prop

When Text Hijacks Vision: Benchmarking and Mitigating Text Overlay-Induced Hallucination in Vision Language Models

arXiv:2604.17375v1 Announce Type: new Abstract: Recent advances in Vision-Language Models (VLMs) have substantially enhanced their ability across multimodal video understanding benchmarks spanning tem

Where to Focus: Query-Modulated Multimodal Keyframe Selection for Long Video Understanding

arXiv:2604.17422v1 Announce Type: new Abstract: Long video understanding remains a formidable challenge for Multimodal Large Language Models (MLLMs) due to the prohibitive computational cost of proces

local-aiarxiv-cs-cv

Beyond Single-Model Optimization: Preserving Plasticity in Continual Reinforcement Learning

arXiv:2604.15414v1 Announce Type: cross Abstract: Continual reinforcement learning must balance retention with adaptation, yet many methods still rely on single-model preservation, committing to one e

local-aiarxiv-cs-ai

DenTab: A Dataset for Table Recognition and Visual QA on Real-World Dental Estimates

arXiv:2604.16099v1 Announce Type: new Abstract: Tables condense key transactional and administrative information into compact layouts, but practical extraction requires more than text recognition: sys

Applications

Evaluating the Progression of Large Language Model Capabilities for Small-Molecule Drug Design

arXiv:2604.16279v1 Announce Type: new Abstract: Large Language Models (LLMs) have the potential to accelerate small molecule drug design due to their ability to reason about information from diverse s

applicationsarxiv-cs-lg

GIST: Multimodal Knowledge Extraction and Spatial Grounding via Intelligent Semantic Topology

arXiv:2604.15495v1 Announce Type: new Abstract: Navigating complex, densely packed environments like retail stores, warehouses, and hospitals poses a significant spatial grounding challenge for humans

local-aiarxiv-cs-ai

Applications

Information Router for Mitigating Modality Dominance in Vision-Language Models

arXiv:2604.16264v1 Announce Type: new Abstract: Vision Language models (VLMs) have demonstrated strong performance across a wide range of benchmarks, yet they often suffer from modality dominance, whe

applicationsarxiv-cs-cv

KRONE: Scalable LLM-Augmented Log Anomaly Detection via Hierarchical Abstraction

arXiv:2602.07303v3 Announce Type: replace-cross Abstract: Log anomaly detection is crucial for uncovering system failures and security risks. Although logs originate from nested component executions w

local-aiarxiv-cs-ai

KWBench: Measuring Unprompted Problem Recognition in Knowledge Work

model-releasesarxiv-cs-ai

arXiv:2604.15760v1 Announce Type: new Abstract: We introduce the first version of KWBench (Knowledge Work Bench), a benchmark for unprompted problem recognition in large language models: can an LLM id

Making Image Editing Easier via Adaptive Task Reformulation with Agentic Executions

arXiv:2604.15917v1 Announce Type: new Abstract: Instruction guided image editing has advanced substantially with recent generative models, yet it still fails to produce reliable results across many se

Robust Fleet Sizing for Multi-UAV Inspection Missions under Synchronized Replacement Demand

arXiv:2604.15890v1 Announce Type: new Abstract: Multi-UAV inspection missions require spare drones to replace active drones during recharging cycles. Existing fleet-sizing approaches often assume stea

researcharxiv-cs-ro

Time-optimal Convexified Reeds-Shepp Paths on a Sphere

arXiv:2504.00966v2 Announce Type: replace Abstract: This article studies the time-optimal path planning problem for a convexified Reeds-Shepp (CRS) vehicle on a unit sphere, capable of both forward an

researcharxiv-cs-ro

UsefulBench: Towards Decision-Useful Information as a Target for Information Retrieval

arXiv:2604.15827v1 Announce Type: cross Abstract: Conventional information retrieval is concerned with identifying the relevance of texts for a given query. Yet, the conventional definition of relevan

When Do Early-Exit Networks Generalize? A PAC-Bayesian Theory of Adaptive Depth

arXiv:2604.15764v1 Announce Type: cross Abstract: Early-exit neural networks enable adaptive computation by allowing confident predictions to exit at intermediate layers, achieving 2-8imes inference s

researcharxiv-cs-ai

Whose Facts Win? LLM Source Preferences under Knowledge Conflicts

arXiv:2601.03746v3 Announce Type: replace Abstract: As large language models (LLMs) are more frequently used in retrieval-augmented generation pipelines, it is increasingly relevant to study their beh

Zoom Consistency: A Free Confidence Signal in Multi-Step Visual Grounding Pipelines

arXiv:2604.15376v1 Announce Type: cross Abstract: Multi-step zoom-in pipelines are widely used for GUI grounding, yet the intermediate predictions they produce are typically discarded after coordinate

researcharxiv-cs-ai

Agents

AMA: Adaptive Memory via Multi-Agent Collaboration