Search: “routing”

In-Expectation Convergence of Stochastic Gradient Methods under Heavy-Tailed Noise

arXiv:2606.00520v1 Announce Type: cross Abstract: Many stochastic gradient methods are believed not to converge when the noise in stochastic gradients has only a finite p-th moment for pinleft(1,2righ

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Safety

KG-FairDiff: Knowledge Graph-Guided Prompt Refinement for Demographically Fair Text-to-Image Generation

DGX agent

arXiv:2606.01282v1 Announce Type: new Abstract: Text-to-Image (TTI) systems are now everyday infrastructure for journalism, education, advertising, and public communication, and the demographic and cu

safetyarxiv-cs-cv

2 Jun 2026

Learning-based Directed Graph Abstraction of Combinatorial Spaces for Order-Preserving Search in Mixed-Combinatorial Nonlinear Optimization

model-releasesarxiv-cs-lg

arXiv:2606.01425v1 Announce Type: new Abstract: Mixed-combinatorial nonlinear programming (MCNLP) problems arise in many engineering design and planning applications, e.g., due to categorical, compone

LLM-Driven Co-Evolutionary Automated Heuristic Design for Bi-Component Coupled Combinatorial Optimization

arXiv:2606.00718v1 Announce Type: new Abstract: While Large Language Models (LLMs) have recently shown promise in Automated Heuristic Design (AHD), existing methods typically generate and evolve heuri

local-aiarxiv-cs-ai

Low-Resource Safety Failures Are Action Failures, Not Representation Failures

arXiv:2606.01196v1 Announce Type: cross Abstract: Safety alignment learned in high-resource languages transfers poorly to low-resource languages. Models refuse harmful prompts in English but fail to r

Model-Based Quality Assessment for Massively Multilingual Parallel Data

arXiv:2606.00285v1 Announce Type: new Abstract: Large-scale multilingual bitext often contains two distinct problems: non-parallel sentence pairs and low-quality translations. We decompose model-based

Multi-Contrast MRI Motion Correction via Parameter-Informed Disentanglement and Adaptive Experts

arXiv:2606.00146v1 Announce Type: cross Abstract: Motion artifacts in magnetic resonance imaging (MRI) degrade diagnostic reliability. Existing deep learning methods are typically contrast-specific an

Hardware

Observation, Not Prediction: Conversation-Level Disaggregated Scheduling for Agentic Serving

arXiv:2606.01839v1 Announce Type: cross Abstract: LLM-based agents resolve a user task through many turns of dependent inference and tool calls, producing a workload whose total cost is unknown when t

hardwarearxiv-cs-lg

Agents

OctoT2I: A Self-Evolving Agentic Text-to-Image Router

arXiv:2606.01803v1 Announce Type: new Abstract: The explosive growth of Text-to-Image (T2I) models, from large-scale versions to lightweight, real-time ones, now faces diminishing marginal returns fro

agentsarxiv-cs-ai

Ontology-Guided Reasoning for Affordance-Based Explanations of Robot Navigation

model-releasesarxiv-cs-ro

arXiv:2606.00117v1 Announce Type: new Abstract: This paper proposes ontology-guided reasoning for affordance-based explanations of robot navigation. In human environments, it is not sufficient for a r

Perception First: A Frontier Native-Video Model with Self-Consistency for Implicit Video Question Answering

model-releasesarxiv-cs-cv

arXiv:2606.01485v1 Announce Type: new Abstract: We describe our submission to the VRR Challenge @ CVPR 2026, built on the ImplicitQA / VRR-QA benchmark~ite{implicitqa}: multiple-choice video question

Physics-Informed Modeling and Control of Emergent Behaviors in Robot Swarms

arXiv:2606.01597v1 Announce Type: new Abstract: Robot swarms can exhibit coherent collective behaviors through local perception, limited communication and decentralized decision-making, yet modeling a

local-aiarxiv-cs-ro

Question-Aware Evidence Ledgers for Video Relational Reasoning

model-releasesarxiv-cs-cv

arXiv:2606.02506v1 Announce Type: new Abstract: The VRR-QA challenge evaluates visual relational reasoning in videos, where answers often depend on implicit spatial relations, event boundaries, target

Agents

TechGraphRAG: An Agentic Graph-Augmented RAG Framework for Technical Literature Reasoning

arXiv:2606.01613v1 Announce Type: cross Abstract: This paper presents an agentic retrieval-augmented generation (RAG) framework for domain-specific technical reasoning support, instantiated over a cur

agentsarxiv-cs-ai

TimeBlocks: Foundational and Continual Time-Series Blockbase -- Extended Version

arXiv:2606.02142v1 Announce Type: new Abstract: The ongoing digitization has led to a proliferation of time-series data streams that monitor a variety of processes, from which valuable insights may be

TLG: Temporal-Logic Grounding for Video Question Answering via Source-Annotation Reconstruction and Category-Targeted Reasoning

model-releasesarxiv-cs-cv

arXiv:2606.01591v1 Announce Type: new Abstract: The TimeLogic Challenge evaluates formal temporal-logic reasoning over video - 16 operators (before, after, until, since, always, co-occur, ordering, ..

VLBM: Variational Latent Basis Modeling for OOD Robust Multivariate Time Series Forecasting

arXiv:2606.02138v1 Announce Type: cross Abstract: Out of distribution (OOD) events in multivariate time series forecasting are rare but often dominate real world risk, making average case forecasting

Applications

Which Institutional Frameworks Do Chatbots Assume? Auditing Jurisdictional Defaults in Multilingual LLMs

arXiv:2606.00333v1 Announce Type: new Abstract: LLMs increasingly answer questions about taxes, labor protections, healthcare, education, pensions, and administrative procedures, where usefulness ofte

applicationsarxiv-cs-cl

A Lecture Note on Offline RL and IRL, Part II: Foundations of Inverse Reinforcement Learning and Dynamic Discrete Choice Models

arXiv:2605.30843v1 Announce Type: new Abstract: In the forward reinforcement-learning problem, the reward is fixed and known; the learner is asked to find a good policy or value function. Here we turn

safetyarxiv-cs-lg

Applications

Astra: a generalizable report generation foundation model for 3D computed tomography

arXiv:2605.31437v1 Announce Type: new Abstract: CT interpretation requires radiologists to review hundreds of volumetric slices per examination, making reporting time-consuming and highly expertise-de

applicationsarxiv-cs-cv

CacheProbe: Auditing Prompt Cache Isolation in Gateway APIs

arXiv:2605.30613v1 Announce Type: cross Abstract: Over the past year, prompt caching in Large Language Models (LLMs) has become increasingly more popular across inference APIs. Prompt caching helps sa

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution

arXiv:2605.30802v1 Announce Type: cross Abstract: Prediction markets aggregate collective intelligence to forecast uncertain events, but their utility depends on reliable outcome resolution. Existing

Eywa: Provenance-Grounded Long-Term Memory for AI Agents

arXiv:2605.30771v1 Announce Type: new Abstract: AI agents that persist across sessions need memory they can retrieve, audit, update, and erase. Existing memory systems often collapse source evidence,

Graph-Conditioned Mixture of Graph Neural Network Experts for Traffic Forecasting

arXiv:2605.30486v1 Announce Type: cross Abstract: Spatio-temporal forecasting on sensor graphs is commonly tackled with a single backbone architecture applied uniformly across all nodes, although grap

Tutorials

Interpretability Without Tradeoffs: Disentangling Polysemanticity At Equal Predictive Performance

arXiv:2605.31304v1 Announce Type: cross Abstract: Deep neural networks (DNNs) are widely used, but interpreting what they actually learn remains difficult. A major obstacle is that individual neurons

tutorialsarxiv-cs-cv

Knowledge Boundary Probing and Demand-Guided Intervention for LLM-Based Power System Code Generation

arXiv:2605.31478v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to automate power-system analysis, but many utilities and energy-research labs require on-premise s

Learning-Based Navigation for Indoor Mobile Robots

model-releasesarxiv-cs-ro

arXiv:2605.30468v1 Announce Type: new Abstract: This paper presents a learning-based navigation framework for indoor mobile robots. The proposed method combines a supervised neural global planner, tra

Learning Whom to Trust: Market-Feedback Adaptive Retrieval for Frozen LLMs in Event-Driven Financial RAG

arXiv:2605.31201v1 Announce Type: new Abstract: Financial retrieval-augmented generation (RAG) systems typically rank evidence by textual relevance, but in financial markets the useful evidence source

On-Device Robotic Planning: Eliminating Inference Redundancy for Efficient Decision-Making

arXiv:2605.31460v1 Announce Type: new Abstract: Reasoning-based robotic policies using large language and vision-language models achieve strong semantic planning capabilities but mostly suffer from a

local-aiarxiv-cs-ro

Applications

OrcaRouter: A Production-Oriented LLM Router with Hybrid Offline-Online Learning

arXiv:2605.30736v1 Announce Type: cross Abstract: The rapid development of large language models, each with distinct capabilities and inference costs, raises a practical deployment question: given an

applicationsarxiv-cs-ai

Rethinking Sparse Mixture of Experts from a Unified Perspective

arXiv:2503.22996v3 Announce Type: replace Abstract: Sparse Mixture of Experts (SMoE) models scale the capacity of models while maintaining constant computational overhead. SMoE methods fall into two c

researcharxiv-cs-cl

Agents

SAGE: A Novelty Gate for Efficient Memory Evolution in Agentic LLMs

arXiv:2605.30711v1 Announce Type: cross Abstract: Agentic LLMs must continuously decide whether newly extracted facts should be added, merged with existing memories, or ignored, yet prior work has foc

agentsarxiv-cs-ai

SlotMemory: Object-Centric KV Memory for Streaming Long-Video Generation

arXiv:2605.31033v1 Announce Type: new Abstract: Streaming video generation models typically rely on temporal-centric memory, which organizes historical context as raw frames, chunk segments, or unclus

researcharxiv-cs-cv

TARIC: Memory-Augmented Traversability-Aware Outdoor VLN under Interrupted Semantic Cues

arXiv:2605.31121v1 Announce Type: cross Abstract: Outdoor vision-language navigation (VLN) in long-range, open-world environments is frequently disrupted by semantic-cue interruptions, where informati

safetyarxiv-cs-ai

Ubiquity of Emergent Hebbian Dynamics in Regularized Learning

arXiv:2505.18069v3 Announce Type: replace Abstract: Hebbian and anti-Hebbian plasticity are widely observed in the brain and are classically modeled as mechanistic, local homosynaptic rules stabilized

safetyarxiv-cs-lg

Value Functions as Supermartingale Certificates

arXiv:2605.31524v1 Announce Type: new Abstract: Certification methods for stochastic systems provide sufficient proof rules, based on real-valued supermartingale certificates, to determine the almost-

safetyarxiv-cs-lg

Vision-Based Localization in Dense Urban Environments: A Case Study of an Urban Village in China

arXiv:2605.30714v1 Announce Type: new Abstract: Urban villages, the widespread informal settlements which have emerged as a result of rapid urbanization, are now major residential hubs for migrant wor

local-aiarxiv-cs-cv

Wall-OSS-0.5 Technical Report

arXiv:2605.30877v1 Announce Type: new Abstract: Large-scale Vision-Language-Action (VLA) pretraining is increasingly adopted as the foundation for robot policies, yet the evidence for pretrained VLAs

safetyarxiv-cs-ro

Bridging the Semantic Gap for Categorical Data Clustering via Large Language Models

arXiv:2601.01162v3 Announce Type: replace-cross Abstract: Qualitative data are widespread in domains such as healthcare, marketing, and bioinformatics, where clustering offers a fundamental tool for p

Coarse-Grained Boltzmann Generators

arXiv:2602.10637v2 Announce Type: replace Abstract: Sampling equilibrium molecular configurations from the Boltzmann distribution is a longstanding challenge. Boltzmann Generators (BGs) address this b

Conformal Certification of Reasoning Trace Prefixes

arXiv:2605.30085v1 Announce Type: new Abstract: Language model reasoning traces are rarely all-or-nothing; they frequently contain valid intermediate steps before a critical error occurs. Existing unc

researcharxiv-cs-ai

ConMoE: Expert-Pool Consolidation via Prototype Reassignment for MoE Compression

arXiv:2605.29350v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) language models reduce per-token computation but still require storing and serving all experts, making deployment memory-intens

Context Distillation as Latent Memory Management

arXiv:2605.28889v1 Announce Type: cross Abstract: Context distillation compresses contextual information into model parameters, yet existing methods often ignore how multiple distilled latent memories

researcharxiv-cs-ai

Do Proactive Agents Really Need an LLM to Decide When to Wake and What to Anchor?

arXiv:2605.30152v1 Announce Type: cross Abstract: Proactive agents read user activity as text and call an LLM on every event to decide whether to act. But user activity is not natively text: it is a s

local-aiarxiv-cs-ai

DynaGraph: Lightweight Multi-Model Interaction Framework via Dynamic Topological Reconfiguration

arXiv:2605.29511v1 Announce Type: cross Abstract: Tackling complex reasoning tasks typically relies on massive monolithic LLMs, which suffer from severe computational redundancy. While task decomposit

local-aiarxiv-cs-cl

Dynamics Within Latent Chain-of-Thought: An Empirical Study of Causal Structure

arXiv:2602.08783v3 Announce Type: replace Abstract: Latent or continuous chain-of-thought methods replace explicit textual rationales with a number of internal latent steps, but these intermediate com

safetyarxiv-cs-ai

Entity-Collision: A Stratified Protocol for Attributing Retrieval Lift in Agent Memory

arXiv:2605.29630v1 Announce Type: cross Abstract: End-to-end agent-memory benchmarks report a single hit@k per retriever, confounding lexical leakage (uncontrolled query/gold/distractor entity overlap

KBF: Knowledge Boundary as Fingerprint for Language Model and Black-Box API Auditing

arXiv:2605.29524v1 Announce Type: cross Abstract: Relay and reseller APIs increasingly intermediate access to large language models (LLMs), but users have no direct way to verify that a claimed endpoi