Search: “agents”

SparseWorld: Enhancing End-to-End Autonomous Driving via World Models with Sparse Scene Representation

model-releasesarxiv-cs-cv

arXiv:2605.24354v2 Announce Type: replace Abstract: Recently, world models have made significant progress in enhancing end-to-end driving systems through both future situation forecasting and improved

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Safety

Statistical Inference for Misspecified Contextual Bandits

DGX agent

arXiv:2606.22639v1 Announce Type: cross Abstract: Contextual bandit algorithms have transformed modern experimentation by enabling real-time adaptation for personalized treatment. Yet these advantages

safetyarxiv-cs-lg

23 Jun 2026

Tutorials

The New Associationism: Lessons from Deep Learning

arXiv:2606.20600v1 Announce Type: cross Abstract: What can the success of modern AI tell us about how humans learn? This paper argues that taking AI seriously as a model of human learning supports a m

tutorialsarxiv-cs-lg

Hardware

The Reservoir Attention Network: Cross-Pass State in Pretrained Transformers via Content-Addressable Reservoir Injection

arXiv:2606.15678v2 Announce Type: replace Abstract: A feasibility and dynamics study of the Reservoir Attention Network (RAN), an architecture that injects a fixed, randomly-initialized reservoir into

hardwarearxiv-cs-lg

What if? Emulative Simulation with World Models for Situated Reasoning

arXiv:2603.06445v2 Announce Type: replace Abstract: Situated reasoning often relies on active exploration, yet in many real-world scenarios such exploration is infeasible due to physical constraints o

safetyarxiv-cs-cv

SAG: SQL-Retrieval Augmented Generation with Query-Time Dynamic Hyperedges

Human

SAG retrieves structured multi-hop evidence via event-entity hyperedges and query-time joins, without a maintained global knowledge graph.

ragsqlmulti-hop

14 Jun 2026

AI4SLT: Empirical Processes in Lean 4 for Formal Statistical Learning Theory

arXiv:2602.02285v2 Announce Type: replace-cross Abstract: We present the first comprehensive Lean 4 formalization of statistical learning theory (SLT) grounded in empirical process theory. Our en-to-e

researcharxiv-cs-cl

Automating Geometry-Intensive Compliance Checking in BIM: Graph-Based Semantic Reasoning Framework

arXiv:2606.12065v1 Announce Type: new Abstract: Automating compliance check for geometry-intensive regulations remains a significant technical bottleneck in Building Information Modeling (BIM), primar

EvoLMM: Self-Evolving Large Multimodal Models with Continuous Rewards

arXiv:2511.16672v4 Announce Type: replace Abstract: Recent advances in large multimodal models (LMMs) have enabled impressive reasoning and perception abilities, yet most existing training pipelines s

researcharxiv-cs-cv

Implicit Neural Representations of Individual Behavior

arXiv:2606.12200v1 Announce Type: cross Abstract: We study policy representation learning from unlabeled multi-policy behavioral data. Each episode is generated by a fixed policy, but policy labels ar

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications

model-releasesarxiv-cs-lg

arXiv:2512.08211v2 Announce Type: replace Abstract: Large language models (LLMs) are moving from cloud-centric services toward on-device embedded AI, where models interact with private, longitudinal s

Reinforcement Learning with Action-Triggered Observations

arXiv:2510.02149v2 Announce Type: replace Abstract: We introduce Action-Triggered Sporadically Traceable Markov Decision Processes (ATST-MDPs), a reinforcement learning framework for partial observabi

safetyarxiv-cs-lg

Sample-Efficient Hypergradient Estimation for Decentralized Bi-Level Reinforcement Learning

arXiv:2603.14867v4 Announce Type: replace-cross Abstract: Many strategic decision-making problems, such as environment design for warehouse robots, can be naturally formulated as bi-level reinforcemen

TAHOE: Text-to-SQL with Automated Hint Optimization from Experience

arXiv:2606.12387v1 Announce Type: cross Abstract: Large Language Models (LLMs) have democratized database access through Text-to-SQL, but moving from prototypes to production remains difficult. Real d

The Algorithm Is Not the Behavior: Learned Priors Override Look-Ahead in a Chess-Playing Neural Network

arXiv:2508.21380v3 Announce Type: replace-cross Abstract: Recent mechanistic work has uncovered learned algorithms within neural networks, from modular arithmetic to search and planning in game-playin

When Does Language Matter? Multilingual Instructions Reveal Step-wise Language Sensitivity in Vision-Language-Action Models

model-releasesarxiv-cs-cl

arXiv:2606.11906v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have shown strong performance in language-conditioned robotic manipulation, yet their robustness to linguistic varia

When Generic Prompt Improvements Hurt: Evaluation-Driven Iteration for LLM Applications

arXiv:2601.22025v2 Announce Type: replace-cross Abstract: Evaluating Large Language Model (LLM) applications differs from conventional software testing because outputs are probabilistic, semantically

Which Models Are Our Models Built On? Auditing Invisible Dependencies in Modern LLMs

model-releasesarxiv-cs-cl

arXiv:2606.12385v1 Announce Type: new Abstract: Modern LLM training pipelines increasingly rely on other models to generate data, filter corpora, judge outputs, and guide development decisions. These

Exploration of Foundation Model-Based Robots in Patient and Elderly Care

arXiv:2606.10208v1 Announce Type: cross Abstract: Demand for older-adult and patient care is growing rapidly as populations age worldwide. Foundation models are increasingly being integrated into robo

researcharxiv-cs-ai

Interactions Between Crosscoder Features: A Compact Proofs Perspective

arXiv:2606.09940v1 Announce Type: cross Abstract: Dictionary learning methods like Sparse Autoencoders (SAEs) and crosscoders attempt to explain a model by decomposing its activations into independent

researcharxiv-cs-ai

LLM-Aided Joint Secrecy Precoding and Trajectory for RSMA-Based Heterogeneous UAV Networks

arXiv:2507.17188v2 Announce Type: replace-cross Abstract: This paper investigates secure communications in rate-splitting multiple access (RSMA) enabled heterogeneous UAV networks, where multiple UAVs

Model-Based Reinforcement Learning in Discrete-Action Non-Markovian Reward Decision Processes

arXiv:2512.14617v2 Announce Type: replace-cross Abstract: Many practical decision-making problems involve tasks whose success depends on the entire system history, rather than on achieving a state wit

researcharxiv-cs-ai

Monte Carlo Pass Search: Using Trajectory Generation for 3D Counterfactual Pass Evaluation in Football

arXiv:2606.11120v1 Announce Type: new Abstract: We recast pass evaluation in football (soccer) as a Monte Carlo Tree Search (MCTS)-like evaluation problem whose components mostly exist in the literatu

SCOPE: Sequential Causal Optimization of Process Interventions

arXiv:2512.17629v4 Announce Type: replace-cross Abstract: Prescriptive Process Monitoring (PresPM) recommends interventions during running business processes to optimize key performance indicators (KP

The Shibboleth Effect: Auditing the Cross-Lingual Distributional Skew of Large Language Models

model-releasesarxiv-cs-cl

arXiv:2606.11082v1 Announce Type: new Abstract: This study investigates cross-lingual distributional skew (the Shibboleth Effect) in frontier large language models (LLMs) subjected to sustained advers

Using Probabilistic Programs to Train Inductive Reasoning in Large Language Models

arXiv:2606.09856v1 Announce Type: cross Abstract: Post-training Large Language Models (LLMs) for reasoning typically focuses on deductive tasks such as mathematics and coding where correctness is veri

When RL Fails after SFT: Rejuvenating Model Plasticity for Robust SFT-to-RL Handoff

arXiv:2606.09932v1 Announce Type: cross Abstract: Supervised Fine-Tuning (SFT) followed by Reinforcement Learning (RL) has become a standard pipeline for Large Language Model (LLM) post-training. SFT

ACTIVE-o3: Empowering MLLMs with Active Perception via Pure Reinforcement Learning

arXiv:2505.21457v2 Announce Type: replace-cross Abstract: Active vision, also known as active perception, refers to actively selecting where and how to look in order to gather task-relevant informatio

An Agency-Transferring Model-Free Policy Enhancement Technique

arXiv:2606.09825v1 Announce Type: cross Abstract: Training reinforcement learning (RL) policies from scratch is costly: it requires careful reward and environment design, extensive tuning, and substan

Local Ai

An Alternative Trajectory for Generative AI

arXiv:2603.14147v2 Announce Type: replace Abstract: The generative artificial intelligence (AI) ecosystem is undergoing rapid transformations that threaten its sustainability. As models transition fro

local-aiarxiv-cs-ai

Artificial Intelligence for Mathematical Reasoning: An Integrated Survey of Language Models, Neuro-symbolic Systems, and Verified Discovery

arXiv:2606.08728v1 Announce Type: new Abstract: Mathematical reasoning has long served as a stringent test of machine intelligence; over the past decade, it has moved from a niche problem within NLP t

Claude Code-Driving Scenario Mining for the Argoverse 2 Challenge

model-releasesarxiv-cs-cv

arXiv:2606.09180v1 Announce Type: new Abstract: We present our submission to the CVPR 2026 Argoverse 2 Scenario Mining Challenge. Our system uses a four-stage pipeline: (1) autonomous code generation

Code Is More Than Text: Uncertainty Estimation for Code Generation

arXiv:2606.09577v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as code generators, where silently wrong programs pose real safety and reliability risks. Relia

safetyarxiv-cs-lg

DIVERGE: Diversity-Enhanced RAG for Open-Ended Information Seeking

arXiv:2602.00238v2 Announce Type: replace-cross Abstract: Existing retrieval-augmented generation (RAG) systems often assume that each query has a single correct answer. This assumption overlooks open

Evaluating AI Investment Strategies

arXiv:2606.08791v1 Announce Type: cross Abstract: We study the problem of auditing a black-box algorithmic decision-maker from observable inputs and outputs alone. Our main result is an exact decompos

Local Ai

Federated Large Language Models: Current Progress and Future Directions

arXiv:2409.15723v3 Announce Type: replace Abstract: Large Language Models have achieved impressive performance across diverse applications, yet their training typically depends on centralized data col

local-aiarxiv-cs-lg

Formalizing Learning from Language Feedback with Provable Guarantees

arXiv:2506.10341v2 Announce Type: replace Abstract: Interactively learning from observation and language feedback is an increasingly studied area driven by the emergence of large language model (LLM)

researcharxiv-cs-lg

HA-VLN 2.0: An Open Benchmark and Leaderboard for Human-Aware Navigation in Discrete and Continuous Environments with Dynamic Multi-Human Interactions

arXiv:2503.14229v4 Announce Type: replace Abstract: Vision-and-Language Navigation (VLN) has been studied mainly in either discrete or continuous spaces, with little attention to dynamic, crowded envi

Harness Engineering for Physical AI: Robot Middleware Is the Harness Layer

arXiv:2606.09416v1 Announce Type: cross Abstract: Robot middleware faces a new role in the era of Physical AI. Learned policies, planners, and vision-language-action (VLA) models now enter deployed ro

Applications

iMaC: Translating Actions into Motion and Contact Images for Embodied World Models

arXiv:2606.09813v1 Announce Type: cross Abstract: Embodied world models have emerged as a pivotal paradigm for visual robotic decision-making and interactive environment simulation. However, conventio

applicationsarxiv-cs-cv

IR-SIM: A Lightweight Skill-Native Simulator for Navigation, Learning, and Benchmarking

arXiv:2606.08729v1 Announce Type: cross Abstract: Simulation plays a key role in automated robotics research supported by large language models (LLMs). However, existing simulators often require custo

safetyarxiv-cs-lg

LUNA-AD: Lightweight Uncertainty-Aware Language Model with Lifelong Learning for Autonomous Driving

arXiv:2606.08470v1 Announce Type: new Abstract: While large language models (LLMs) offer promising reasoning capabilities, their integration into safety-critical driving systems is hindered by limited

safetyarxiv-cs-ro

PRISM: PRior-guided Imagination Sampling in world Models

arXiv:2606.07974v1 Announce Type: cross Abstract: A learned world model provides a powerful physical intuition for evaluating future states. But its effectiveness in continuous control also depends cr

Repair Before Veto, When Repair Is Hidden: Quantum-Accessible Features for Repair-Augmented Constraint Learning

arXiv:2606.08020v1 Announce Type: cross Abstract: Hard-constraint decision systems usually veto infeasible candidates. This is too rigid when the system can act: if a known affordable repair would mak

SciFlow-Bench: Evaluating Structure-Aware Scientific Diagram Generation via Inverse Parsing

model-releasesarxiv-cs-cv

arXiv:2602.09809v2 Announce Type: replace Abstract: Scientific diagrams convey explicit structural information, yet modern text-to-image models often produce visually plausible but structurally incorr

SLMJury: Can Small Language Models Judge as Well as Large Ones?

arXiv:2606.07810v1 Announce Type: cross Abstract: Large language models (LLMs) are widely used as judges for evaluating model outputs, but their high cost, latency, and opacity limit scalability. We i

SynManDex: Synthesizing Human-like Dexterous Grasps from Synthetic Human Pre-Grasps

arXiv:2606.09798v1 Announce Type: new Abstract: Human hand-object interactions encode functional intent, but direct transfer to robotic hands often fails under morphology, contact, and reachability co

researcharxiv-cs-ro

Systems-Level Planning and Coordination of Truck-Drone Collaborative Delivery Networks

arXiv:2606.08738v1 Announce Type: cross Abstract: Urban last-mile parcel delivery increasingly relies on heterogeneous fleets whose performance depends on timely coordination, reliable communication,

safetyarxiv-cs-ro