Search: “framework”

AllDayNav: Lifelong Navigation via Real-World Reinforcement Learning

arXiv:2606.10927v1 Announce Type: new Abstract: Lifelong embodied navigation in dynamic environments requires robots to form persistent scene understanding from fragmentary observations, which remains

applicationsarxiv-cs-ro

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AnomaMind: Agentic Time Series Anomaly Detection with Tool-Augmented Reasoning

DGX agent

arXiv:2602.13807v2 Announce Type: replace Abstract: Time series anomaly detection is critical in many real-world applications, where effective solutions must localize anomalous regions and support rel

local-aiarxiv-cs-lg

10 Jun 2026

AnyMod-LLVE: Low-Light Video Enhancement with Modality-Agnostic Inference

arXiv:2606.11186v1 Announce Type: new Abstract: Low-light video enhancement (LLVE) remains a challenging task due to severe information degradation under low-illumination conditions. Recent multimodal

applicationsarxiv-cs-cv

Architect-Ant: Editable Automatic Furnishing of Architectural Floor Plans

arXiv:2606.10953v1 Announce Type: new Abstract: Furnished floor plans are fundamental to real estate visualization, interior design, and architectural workflows. However, progress in automatic furnitu

Are We Evaluating Knowledge or Phrasing? Mitigating MCQA Sensitivity with ParaEval

arXiv:2606.10657v1 Announce Type: new Abstract: Multiple-choice (MCQA) benchmarks are the standard for evaluating pretrained large language models, but their reliance on log-likelihood scoring makes t

researcharxiv-cs-cl

ARM: An AutoRegressive Large Multimodal Model with Unified Discrete Representations

arXiv:2606.11188v1 Announce Type: new Abstract: This paper introduces ARM, a discrete representation-based AutoRegressive Model that unifies image understanding, generation, and editing within a next-

safetyarxiv-cs-cv

Assessing Automated Prompt Injection Attacks in Agentic Environments

arXiv:2606.10525v1 Announce Type: cross Abstract: Indirect prompt injection poses a critical threat to LLM agents that interact with untrusted external data, yet automated attack methods--proven effec

Atomic Intent Reasoning: Bringing LLM Semantics to Industrial Cross-Domain Recommendations

arXiv:2606.10357v1 Announce Type: cross Abstract: Cross-domain recommendation is a core problem in content-to-e-commerce platforms. Its objective is to leverage user interactions with content to infer

applicationsarxiv-cs-ai

Automated Alignment between Elicitation Interviews and Requirements

arXiv:2510.08622v2 Announce Type: replace Abstract: Software requirements are derived from a variety of elicitation techniques, many of which have a conversational nature, like interviews. However, ev

safetyarxiv-cs-cl

Automated Scoring of Arabic Text Using Large Language Models: A Literature Review

arXiv:2606.09830v1 Announce Type: new Abstract: In modern educational systems, Automatic Text Scoring (ATS) plays a central role by enabling scalable and consistent evaluation of learner responses wit

safetyarxiv-cs-cl

BadRobot: Jailbreaking Embodied LLM Agents in the Physical World

arXiv:2407.20242v5 Announce Type: replace-cross Abstract: Embodied AI represents systems where AI is integrated into physical entities. Large Language Model (LLM), which exhibits powerful language und

Baseline-Free Policy Optimization for Neural Combinatorial Optimization

arXiv:2606.10321v1 Announce Type: cross Abstract: Neural combinatorial optimization (NCO) trains autoregressive policies to solve routing problems. The standard training algorithm, REINFORCE with a ro

Belief-Space Control for Personalized Cancer Treatment via Active Inference

arXiv:2606.10376v1 Announce Type: new Abstract: Cancer treatment is at the core a sequential decision-making problem with partial observability, latent patient heterogeneity, and explicit constraints

Benchmarking Knowledge Editing using Logical Rules

arXiv:2606.10554v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly deployed in real-world applications that require access to up-to-date knowledge. However, retraining LLM

Beyond Absolute Imitation: Anchored Residual Guidance for Privileged On-Policy Distillation

arXiv:2606.10385v1 Announce Type: cross Abstract: On-policy distillation (OPD) has demonstrated strong empirical gains in enhancing complex reasoning in LLMs by aligning a student model with a teacher

local-aiarxiv-cs-ai

Beyond Explaining Predictions: Logic-Based Explanations for Confidence in Machine Learning Models

arXiv:2606.10347v1 Announce Type: new Abstract: Machine learning is increasingly used in critical domains, where both predictions and their associated confidence levels influence important decisions.

Agents

Beyond Static Evaluation: Co-Evolutionary Mechanisms for LLM-Driven Strategy Evolution in Adversarial Games

arXiv:2606.10389v1 Announce Type: new Abstract: Recent advances in LLM-driven code evolution have enabled automated discovery by iteratively generating and improving programs. However, applying these

agentsarxiv-cs-ai

Tutorials

Breaking the Curse of Dimensionality: Diffusion Models Efficiently Learn Low-Dimensional Distributions

arXiv:2409.02426v5 Announce Type: replace-cross Abstract: Despite their empirical success across a wide range of generative tasks, the fundamental principles underlying the ability of diffusion models

tutorialsarxiv-cs-cv

Agents

Business World Model

arXiv:2606.10044v1 Announce Type: new Abstract: Businesses are increasingly adopting AI-enabled tools to improve productivity, reduce costs, and enhance products and services. However, the transformat

agentsarxiv-cs-ai

CapStARE: Capsule-based Sequential Architecture for Robust and Efficient Gaze Estimation

arXiv:2509.19936v2 Announce Type: replace Abstract: Human gaze estimation is essential for applications such as human-computer interaction, social robotics, and assistive systems. However, achieving a

local-aiarxiv-cs-cv

Causal Ensemble Agent: Hierarchical Causal Discovery with LLM-guided Expert Reweighting

arXiv:2606.10607v1 Announce Type: cross Abstract: Causal discovery aims to uncover causal structures from observational data, which is crucial for real-world decision-making. However, different causal

CGES: Confidence-Guided Early Stopping for Efficient and Accurate Self-Consistency

arXiv:2511.02603v2 Announce Type: replace Abstract: Large language models (LLMs) are often queried multiple times at test time, with predictions aggregated by majority vote. While effective, this self

researcharxiv-cs-cl

CleanPatrick: A Benchmark for Image Data Cleaning

arXiv:2505.11034v2 Announce Type: replace-cross Abstract: Robust machine learning depends on clean data, yet current image data cleaning benchmarks rely on synthetic noise or narrow human studies, lim

@ClementDelangue @Dan_Jeffries1 Everyone, please join Project Tapestry https://thealliance.ai/projects/tapestry

Project Tapestry is an initiative under The Alliance focused on collaborative AI development, promoted by prominent AI researchers including Yann LeCun. The project appears to be soliciting participat

researchyann-lecun--x

CodeAlchemy: Synthetic Code Rewriting at Scale

model-releasesarxiv-cs-cl

arXiv:2606.10087v1 Announce Type: new Abstract: Pre-training on raw code teaches syntax but provides sparse signal for diverse real-world task formats. While synthetic data has proven transformative f

COGENT: Continuous Graph Emulators with Neural Ordinary Differential Equations for Long-Term Physical Forecasting

arXiv:2606.11162v1 Announce Type: new Abstract: In this work, we present COGENT, a continuous graph emulator with Neural Ordinary Differential Equations for long-term physical forecasting on irregular

local-aiarxiv-cs-lg

CollabSkill: Evaluating Human-Agent Collaboration On Real-World Tasks

arXiv:2606.09833v1 Announce Type: cross Abstract: AI agents are reshaping the workspace, leading to drastic change of how humans work. Despite the considerable potential of human-agent collaboration b

Compositional Generative Modeling from Decentralized Data

arXiv:2606.10153v1 Announce Type: new Abstract: Learning the compositional nature of the physical world requires joint observation of interacting factors. However, because practical data is often dece

Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation

arXiv:2606.09923v1 Announce Type: cross Abstract: Neural operators such as the Fourier Neural Operator (FNO) have emerged as powerful surrogates for solving partial differential equations (PDEs), achi

Conformal Risk Prediction for Non-Alcoholic Fatty Liver Disease Using Gradient Boosting with Distribution-Free Coverages

arXiv:2606.09860v1 Announce Type: cross Abstract: Non-alcoholic fatty liver disease (NAFLD) affects roughly 25% of global adults, posing substantial hepatic and cardiovascular risks. Yet, population-l

Conservation Laws from Data Symmetry in Neural Networks

arXiv:2606.10913v1 Announce Type: new Abstract: We explore whether intrinsic symmetries of the training data lead to conserved quantities during gradient-flow training of neural networks. Under the as

Cost-Aware Routing for Efficient Text-To-Image Generation

arXiv:2506.14753v3 Announce Type: replace Abstract: Diffusion models are well known for their ability to generate a high-fidelity image for an input prompt through an iterative denoising process. Unfo

researcharxiv-cs-cv

Culturally-Aware AI for Cross-Boundary Community Learning: Undergraduate Innovation at the Intersection of Computation and Design

arXiv:2606.09041v1 Announce Type: cross Abstract: Research on artificial intelligence in education (AIED) is rapidly expanding, yet technical progress often lacks human-centered grounding and adequate

applicationsarxiv-cs-ai

Data-Driven Runway and Taxiway Exits Prediction of Landing Aircraft: A Case Study at Hartsfield-Jackson Atlanta International Airport

model-releasesarxiv-cs-lg

arXiv:2606.11017v1 Announce Type: new Abstract: Airport surface operations increasingly constrain performance at high-throughput hubs. This study examines arrival taxi-in decisions at Hartsfield-Jacks

Agents

Data Journalist Agent: Transforming Data into Verifiable Multimodal Stories

arXiv:2606.11176v1 Announce Type: cross Abstract: Data tells stories that shape society; the data journalist's job is to turn raw information into stories non-experts can trust. A high-quality news fe

agentsarxiv-cs-cl

Decentralized Multi-Agent Systems with Shared Context

arXiv:2606.10662v1 Announce Type: cross Abstract: Multi-agent systems (MAS) can scale large language model reasoning at test time by decomposing complex problems into parallel subtasks. However, most

local-aiarxiv-cs-ai

Deep Generative Model for Human Mobility Behavior

arXiv:2510.06473v3 Announce Type: replace-cross Abstract: Understanding and modeling human mobility is central to challenges in transport planning, sustainable urban design, and public health. Despite

Tutorials

Dep-LLM: Training-Free Depression Diagnosis via Evidence-Guided Structured Multi-factor with Reliable LLM Reasoning

arXiv:2606.10796v1 Announce Type: cross Abstract: Automatic Depression Detection (ADD) from clinical interviews is a pivotal task in computational mental health, yet it remains challenging due to two

tutorialsarxiv-cs-ai

Dexterous Point Policy: Learning Point-based Dexterous Hand Policies from Human Demonstrations

arXiv:2606.10614v1 Announce Type: cross Abstract: Robotic foundation models pre-trained on human demonstration videos have shown promise, but a significant embodiment gap remains when the resulting po

safetyarxiv-cs-cv

Diffusion Forcing Planner: History-Annealed Planning with Time-Dependent Guidance for Autonomous Driving

arXiv:2606.11019v1 Announce Type: cross Abstract: Learning-based motion planners, despite recent progress, often suffer from temporal inconsistency. Small perturbations across frames can accumulate in

Dirichlet-Guided Group Forecasting for Alleviating Over-smoothing in Time Series Forecasting

arXiv:2606.10592v1 Announce Type: new Abstract: Time series forecasting often suffers from over-smoothing, especially when future dynamics are multi-modal. Forecasts may follow the coarse trend of the

applicationsarxiv-cs-lg

Divide and Cooperate: Role-Decomposed Multi-Agent LLM Training with Cross-Agent Learning Signals

arXiv:2606.10684v1 Announce Type: cross Abstract: Modern language agents which perform multi-step reasoning have shown strong performance in knowledge-intensive question answering. However, existing a

Dual-Branch Gated Fusion for Open-Set Audio Deepfake Source Tracing

arXiv:2606.10223v1 Announce Type: cross Abstract: Attributing a synthetic utterance to its originating system remains an open challenge: closed-set models fail to reject unseen synthesizers and produc

DUET -- Dual User Embedding Transformers for Offsite Conversion Prediction

arXiv:2606.10243v1 Announce Type: new Abstract: Offsite conversion rate (OCVR) prediction is an important ranking problem in computational recommendation systems. This task presents a modeling challen

Dynamic Linear Attention

arXiv:2606.10650v1 Announce Type: cross Abstract: The scalability of Large Language Models (LLMs) to long contexts is fundamentally constrained by the quadratic complexity of standard attention, motiv

Early-Token Confidence Predicts Reasoning Quality in Multi-Agent LLM Debate

arXiv:2606.10307v1 Announce Type: new Abstract: Evaluating reasoning quality in multi-agent LLM systems is challenging, especially for open-ended tasks without reference answers. We investigate whethe

safetyarxiv-cs-cl

Earth-OneVision: Extending Remote Sensing Multimodal Large Language Models to More Sensor Modalities and Tasks

arXiv:2606.10819v1 Announce Type: cross Abstract: RS-MLLMs enable natural-language understanding and spatial reasoning over earth observation imagery. However, existing models support only a narrow ra

Efficient RWKV-based Representation Learning for 3D Point Clouds

model-releasesarxiv-cs-cv

arXiv:2606.10395v1 Announce Type: new Abstract: The recent receptance weighted key value (RWKV) model combines RNN-style recurrence, offering a linear-complexity alternative to Transformers' quadratic