Search: “reasoning”

DexJoCo: A Benchmark and Toolkit for Task-Oriented Dexterous Manipulation on MuJoCo

model-releasesarxiv-cs-ro

arXiv:2605.16257v1 Announce Type: new Abstract: Achieving human-level manipulation requires dexterous robotic hands capable of complex object interactions. Advancing such capabilities further demands

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DiffVAS: Diffusion-Guided Visual Active Search in Partially Observable Environments

DGX agent

arXiv:2605.15519v1 Announce Type: cross Abstract: Visual active search (VAS) has been introduced as a modeling framework that leverages visual cues to direct aerial (e.g., UAV-based) exploration and p

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18 May 2026

DimMem: Dimensional Structuring for Efficient Long-Term Agent Memory

arXiv:2605.15759v1 Announce Type: new Abstract: Large language model (LLM) agents require long-term memory to leverage information from past interactions. However, existing memory systems often face a

Do Chinese models speak Chinese languages?

arXiv:2504.00289v3 Announce Type: replace-cross Abstract: The release of top-performing open-weight LLMs has cemented China's role as a leading force in AI development. Do these models support languag

researcharxiv-cs-ai

Ensemble Monitoring for AI Control: Diverse Signals Outweigh More Compute

arXiv:2605.15377v1 Announce Type: new Abstract: As AI systems are increasingly deployed in autonomous agentic settings at scale, it is important to ensure the actions they take are safe and aligned wi

Formal Methods Meet LLMs: Auditing, Monitoring, and Intervention for Compliance of Advanced AI Systems

arXiv:2605.16198v1 Announce Type: new Abstract: We examine one particular dimension of AI governance: how to monitor and audit AI-enabled products and services throughout the AI development lifecycle,

From Failure to Feedback: Group Revision Unlocks Hard Cases in Object-Level Grounding

arXiv:2605.15951v1 Announce Type: new Abstract: Finetuning Large Vision-Language Models with reinforcement learning has emerged as a promising approach to enhance their capability in object-level grou

researcharxiv-cs-cv

GenAI-Driven Approach to RISC-V Supply Chain Exploration

arXiv:2605.15223v1 Announce Type: cross Abstract: This paper presents an LLM-empowered workflow for RISC-V supply chain analysis, integrating Vision-Language Models (VLMs) and Model-Driven Engineering

researcharxiv-cs-ai

Hierarchical and Holistic Open-Vocabulary Functional 3D Scene Graphs for Indoor Spaces

model-releasesarxiv-cs-cv

arXiv:2605.15753v1 Announce Type: cross Abstract: Functional 3D scene graphs offer a versatile and flexible representation for 3D scene understanding and robotic manipulation, defined by object nodes,

Honey, I shrunk the hypothesis space (through logical preprocessing)

arXiv:2506.06739v3 Announce Type: replace Abstract: Inductive logic programming (ILP) is a form of logical machine learning. The goal is to search a hypothesis space for a hypothesis that generalises

researcharxiv-cs-ai

Local Ai

Learning Where It Matters: Geometric Anchoring for Robust Preference Alignment

arXiv:2602.04909v3 Announce Type: replace Abstract: Direct Preference Optimization (DPO) and related methods align large language models from pairwise preferences by regularizing updates against a fix

local-aiarxiv-cs-lg

LLM-EDT: Large Language Model Enhanced Cross-domain Sequential Recommendation with Dual-phase Training

arXiv:2511.19931v2 Announce Type: replace-cross Abstract: Cross-domain Sequential Recommendation (CDSR) has been proposed to enrich user-item interactions by incorporating information from various dom

LPDS: Evaluating LLM Robustness Through Logic-Preserving Difficulty Scaling

arXiv:2605.15393v1 Announce Type: new Abstract: As large language models (LLMs) are increasingly deployed to perform tasks with minimal human oversight, it is crucial that these models operate robustl

researcharxiv-cs-lg

Mind the Motions: Benchmarking Theory-of-Mind in Everyday Body Language

arXiv:2511.15887v2 Announce Type: replace Abstract: Our ability to interpret others' mental states through nonverbal cues (NVCs) is fundamental to our survival and social cohesion. While existing Theo

researcharxiv-cs-cl

Multi-Probe Zero Collision Hash (MPZCH): Mitigating Embedding Collisions and Enhancing Model Freshness in Large-Scale Recommenders

model-releasesarxiv-cs-lg

arXiv:2602.17050v3 Announce Type: replace Abstract: Embedding tables are critical components of large-scale recommendation systems, facilitating the efficient mapping of high-cardinality categorical f

NavRL++: A System-Level Framework for Improving Sim-to-Real Transfer in Reinforcement Learning-Based Robot Navigation

arXiv:2605.15559v1 Announce Type: new Abstract: Recent years have witnessed significant progress in autonomous navigation using reinforcement learning. However, existing approaches largely emphasize r

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Neural Activation Patterns Across Language Model Architectures: A Comprehensive Analysis of Cognitive Task Performance

arXiv:2605.15436v1 Announce Type: new Abstract: This paper presents a comprehensive analysis of neural activation patterns across six distinct large language model (LLM) architectures, examining their

researcharxiv-cs-cl

Offline Reinforcement Learning with Universal Horizon Models

arXiv:2605.15603v1 Announce Type: cross Abstract: Model-based reinforcement learning (RL) offers a compelling approach to offline RL by enabling value learning on imagined on-policy trajectories. Howe

OmniVL-Guard: Towards Unified Vision-Language Forgery Detection and Grounding via Balanced RL

arXiv:2602.10687v3 Announce Type: replace-cross Abstract: Existing forgery detection methods are often limited to uni-modal or bi-modal settings, failing to handle the interleaved text, images, and vi

PBT-Bench: Benchmarking AI Agents on Property-Based Testing

arXiv:2605.15229v1 Announce Type: cross Abstract: Existing code benchmarks measure whether an agent can produce any test that reproduces a known bug, or whether it can produce a patch that fixes a des

PSD: Pushing the Pareto Frontier of Diffusion LLMs via Parallel Speculative Decoding

arXiv:2605.15609v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) generate text by iteratively denoising masked token sequences. Although dLLMs can predict all masked positions i

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Quantum Artificial Intelligence for Mission-Critical Systems: Foundations, Architectural Elements, and Future Directions

arXiv:2511.09884v2 Announce Type: replace Abstract: Mission critical (MC) applications such as defense operations, energy management, cybersecurity, and aerospace control require reliable, determinist

Local Ai

Rethinking Predictive Modeling for LLM Routing: When Simple kNN Beats Complex Learned Routers

arXiv:2505.12601v2 Announce Type: replace Abstract: As large language models (LLMs) grow in scale and specialization, routing--selecting the best model for a given input--has become essential for effi

local-aiarxiv-cs-lg

Reversing the Flow: Generation-to-Understanding Synergy in Large Multimodal Models

arXiv:2605.15792v1 Announce Type: new Abstract: The long-standing goal of multimodal AI is to build unified models in which visual understanding and visual generation mutually enhance one another. Des

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Syntax Without Semantics: Teaching Large Language Models to Code in an Unseen Language

arXiv:2605.15607v1 Announce Type: new Abstract: Large language models (LLMs) achieve high pass rates on code generation benchmarks, yet whether they can transfer this ability to languages absent from

researcharxiv-cs-cl

TopoEvo: A Topology-Aware Self-Evolving Multi-Agent Framework for Root Cause Analysis in Microservices

arXiv:2605.15611v1 Announce Type: new Abstract: Root cause analysis (RCA) in microservices is challenging due to (i) noisy and heterogeneous multimodal observability (metrics, logs, traces), (ii) casc

UAM: A Dual-Stream Perspective on Forgetting in VLA Training

arXiv:2605.15735v1 Announce Type: cross Abstract: Vision--language--action (VLA) models are typically built by fine-tuning a pretrained vision--language model (VLM) on action data. However, we show th

Unlocking Dense Metric Depth Estimation in VLMs

model-releasesarxiv-cs-cv

arXiv:2605.15876v1 Announce Type: new Abstract: Vision-Language Models (VLMs) excel at 2D tasks such as grounding and captioning, yet remain limited in 3D understanding. A key limitation is their text

Unveiling the Black Box: A Multi-Layer Framework for Explaining Reinforcement Learning-Based Cyber Agents

arXiv:2505.11708v3 Announce Type: replace-cross Abstract: Reinforcement Learning (RL) agents are increasingly used to simulate sophisticated cyberattacks, but their decision-making processes remain op

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VCG-Bench: Towards A Unified Visual-Centric Benchmark for Structured Generation and Editing

arXiv:2605.15677v1 Announce Type: new Abstract: Despite the rapid advancements in Vision-Language Models (VLMs), a critical gap remains in their ability to handle structured, controllable diagrammatic

Local Ai

VLMs Trace Without Tracking: Diagnosing Failures in Visual Path Following

arXiv:2605.15672v1 Announce Type: cross Abstract: Vision-language models (VLMs) achieve strong performance on multimodal benchmarks, but may still lack robust control over basic visual operations. We

local-aiarxiv-cs-ai

VSPO: Vector-Steered Policy Optimization for Behavioral Control

arXiv:2605.15604v1 Announce Type: cross Abstract: Modern language models often need to optimize a primary accuracy objective while also accommodating secondary behavioral preferences, such as verbosit

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What Is Preference Optimization Doing, and Why?

arXiv:2512.00778v2 Announce Type: replace Abstract: Preference optimization (PO) is indispensable for large language models (LLMs), with methods such as direct preference optimization (DPO) and proxim

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When Importance Sampling Misallocates Credit: Asymmetric Ratios for Outcome-Supervised RL

arXiv:2510.06062v2 Announce Type: replace Abstract: Reinforcement learning (RL) has shown great promise in large language models (LLMs) post-training, which typically rely on token-level clipping to m

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A Two-Dimensional Framework for AI Agent Design Patterns: Cognitive Function and Execution Topology

arXiv:2605.13850v1 Announce Type: new Abstract: Existing frameworks for LLM-based agent architectures describe systems from a single perspective: industry guides (Anthropic, Google, LangChain) focus o

Agentic AI Ecosystems in Higher Education: A Perspective on AI Agents to Emerging Inclusive, Agentic Multi-Agent AI Framework for Learning, Teaching and Institutional Intelligence

arXiv:2605.14266v1 Announce Type: new Abstract: Integration of artificial intelligent (AI) agents in higher education is transforming teaching, learning and administrative processes. Although existing

Agentifying Patient Dynamics within LLMs through Interacting with Clinical World Model

arXiv:2605.14723v1 Announce Type: new Abstract: Sepsis management in the ICU requires sequential treatment decisions under rapidly evolving patient physiology. Although large language models (LLMs) en

Analogical Trajectory Transfer

arXiv:2605.14393v1 Announce Type: new Abstract: We study analogical trajectory transfer, where the goal is to translate motion trajectories in one 3D environment to a semantically analogous location i

researcharxiv-cs-cv

Attention-Based Multimodal Survival Prediction with Cross-Modal Bilinear Fusion

model-releasesarxiv-cs-lg

arXiv:2605.13897v1 Announce Type: cross Abstract: We propose a novel multimodal deep learning framework for patient-level survival prediction, which integrates whole-slide histology features, RNA-seq

Automated Construction of a Knowledge Graph of Nuclear Fusion Energy for Effective Elicitation and Retrieval of Information

arXiv:2504.07738v3 Announce Type: replace Abstract: In this document, we discuss a multi-step approach to automated construction of a knowledge graph, for structuring and representing domain-specific

Average Gradient Outer Product in kernel regression provably recovers the central subspace for multi-index models

arXiv:2605.15082v1 Announce Type: cross Abstract: We study a prototypical situation when a learned predictor can discover useful low-dimensional structure in data, while using fewer samples than are n

researcharxiv-cs-lg

Beyond Mode-Seeking RL: Trajectory-Balance Post-Training for Diffusion Language Models

arXiv:2605.13935v1 Announce Type: cross Abstract: Diffusion language models are a promising alternative to autoregressive models, yet post-training methods for them largely adapt reward-maximizing obj

ChromaFlow: A Negative Ablation Study of Orchestration Overhead in Tool-Augmented Agent Evaluation

arXiv:2605.14102v1 Announce Type: new Abstract: Autonomous language-model agents increasingly combine planning, tool use, document processing, browsing, code execution, and verification loops. These c

COAL: Counterfactual and Observation-Enhanced Alignment Learning for Discriminative Referring Multi-Object Tracking

arXiv:2605.14795v1 Announce Type: new Abstract: Referring Multi-Object Tracking (RMOT) faces a fundamental structural contradiction between the high-discriminability demand and the sparse semantic sup

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Cognitive-Uncertainty Guided Knowledge Distillation for Accurate Classification of Student Misconceptions

arXiv:2605.14752v1 Announce Type: cross Abstract: Accurately identifying student misconceptions is crucial for personalized education but faces three challenges: (1) data scarcity with long-tail distr

Collider-Bench: Benchmarking AI Agents with Particle Physics Analysis Reproduction

arXiv:2605.13950v1 Announce Type: cross Abstract: Autonomous language-model agents are increasingly evaluated on long-horizon tool-use tasks, but existing benchmarks rarely capture the complexity and

Communication-Efficient Federated Fine-Tuning

model-releasesarxiv-cs-lg

arXiv:2505.04535v3 Announce Type: replace Abstract: Federated Learning (FL) enables the utilization of vast, previously inaccessible data sources. At the same time, pre-trained Language Models (LMs) h

Concurrency without Model Changes: Future-based Asynchronous Function Calling for LLMs

arXiv:2605.15077v1 Announce Type: cross Abstract: Function calling, also known as tool use, is a core capability of modern LLM agents but is typically constrained by synchronous execution semantics. U