Search: “models”

Data Scaling Laws in Imitation Learning for Robotic Manipulation

arXiv:2410.18647v4 Announce Type: replace Abstract: Data scaling has revolutionized fields like natural language processing and computer vision, providing models with remarkable generalization capabil

safetyarxiv-cs-ro

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Dismantling Pathological Shortcuts: A Causal Framework for Faithful LVLM Decoding

DGX agent

arXiv:2606.27596v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) exhibit sophisticated reasoning but remain susceptible to object hallucination. Deviating from the prevailing att

researcharxiv-cs-ai

29 Jun 2026

Distribution-based deep multiple instance learning for tumor proportion scoring in NSCLC

arXiv:2606.27579v1 Announce Type: cross Abstract: Accurate assessment of tumor proportion score (TPS) in non-small cell lung cancer (NSCLC) is critical for treatment planning and prognosis. Key challe

Enhancing Numerical Prediction in LLMs via Smooth MMD Alignment

arXiv:2606.27731v1 Announce Type: cross Abstract: Despite their strong general capabilities, large language models (LLMs) often remain unreliable when outputs must be numerically precise. A key reason

local-aiarxiv-cs-ai

ET-SAM: Efficient Point Prompt Prediction in SAM for Unified Scene Text Detection and Layout Analysis

arXiv:2603.25168v2 Announce Type: replace Abstract: Previous works based on Segment Anything Model (SAM) have achieved promising performance in unified scene text detection and layout analysis. Howeve

Fair Classification with Efficient and Post-hoc Controllable Fairness-Accuracy Trade-off

arXiv:2606.28097v1 Announce Type: new Abstract: Post-hoc controllability of fair machine learning models, the ability to control the trade-off between fairness and accuracy after training, is valuable

safetyarxiv-cs-lg

From General-Purpose Audio Tagging to Spatially Grounded Sound Event Localization and Detection

arXiv:2606.27751v1 Announce Type: cross Abstract: This report investigates the extension of pretrained General-Purpose Audio Tagging (GP-AT) models toward spatially grounded Sound Event Localization a

'Generate' the Future of Work through AI: Empirical Evidence from Online Labor Markets

arXiv:2308.05201v4 Announce Type: replace Abstract: Large Language Model (LLM)-based generative AI systems are general-purpose tools capable of augmenting or even automating a wide range of job functi

GNBAN: Graph Neural Basis Attention Networks for Long-Horizon Forecasting over Large Entity Sets

arXiv:2606.27863v1 Announce Type: cross Abstract: Demand forecasting at the bottom of a retail hierarchy requires predicting tens of thousands of correlated long-horizon series across products, stores

Tutorials

Latent Visual Diffusion Reasoning with Monte Carlo Tree Search

arXiv:2606.27988v1 Announce Type: new Abstract: Analyzing fine-grained skill activities (e.g., sports, surgery) requires not only recognizing visual patterns but also performing step-by-step visual re

tutorialsarxiv-cs-cv

Learn Structure, Adapt on the Fly: Multi-Scale Residual Learning and Online Adaptation for Aerial Manipulators

arXiv:2603.11638v2 Announce Type: replace Abstract: Autonomous Aerial Manipulators (AAMs) are inherently coupled, nonlinear systems that exhibit nonstationary and multiscale residual dynamics, particu

agentsarxiv-cs-ro

Learning Stable In-Grasp Manipulation in a Non-Dropping Action Space

arXiv:2606.28196v1 Announce Type: new Abstract: Traditionally, dexterous manipulation controllers are designed using analytic models constrained by strong assumptions about the hand and the objects be

researcharxiv-cs-ro

Learning to Reason with Curriculum II: Compositional Generalization

arXiv:2606.27721v1 Announce Type: new Abstract: Compositional generalization, the ability to solve complex problems by combining solutions to simpler sub-problems, is a fundamental capability of both

Learning to Refine Hidden States for Reliable LLM Reasoning

arXiv:2606.17524v2 Announce Type: replace Abstract: Large language models show strong reasoning ability, but their internal reasoning process can remain unstable in complex multi-step settings, where

safetyarxiv-cs-lg

Mechanism-Driven Monitors for Preemptive Detection of LLM Training Instability

arXiv:2606.28116v1 Announce Type: new Abstract: Frontier large language model training consumes massive accelerator fleets and long wall-clock computation, making stability failures costly when they o

researcharxiv-cs-cl

MindFlow: Harmonizing Cognitive Semantics and Acoustic Dynamics for Facial Animation Generation in Dyadic Conversations

arXiv:2606.27779v1 Announce Type: new Abstract: Generating lifelike facial animation for dyadic conversations requires reconciling high-level cognitive intent with precise low-level motor reflexes, ye

MixTTA: Low-Rank Cross-Channel Mixing for Reliable Test-Time Adaptation

arXiv:2606.28142v1 Announce Type: new Abstract: Test-Time Adaptation (TTA) methods commonly update the affine parameters of normalization layers to adapt deployed models under distribution shifts. How

NLL-Guided Full-Attention Layer Selection for Training-Free Sliding-Window Adaptation

arXiv:2606.27791v1 Announce Type: cross Abstract: Hybrid attention models that mix full and sliding-window attention across layers offer a promising approach to efficient long-context inference, but t

OperatorSHAP: Fast and Accurate Shapley Value Estimation for Neural Operators

arXiv:2606.28065v1 Announce Type: cross Abstract: Understanding model predictions is essential for physical applications, where outputs often inform safety-critical decisions, such as structural load

OSOR: One-Step Diffusion Inpainting for Effect-Aware Object Removal

arXiv:2606.28094v1 Announce Type: cross Abstract: Real-world object removal is challenging due to two key difficulties: the target object's non-local effects, such as shadows and reflections, which ar

local-aiarxiv-cs-ai

Physics-Guided Robotic Radiation Source Localization along Arbitrary Measurement Paths in Unstructured Environments

arXiv:2606.27624v1 Announce Type: cross Abstract: Using robots to estimate the location of the radiation source is an effective way to improve efficiency and safety. Existing methods focus on planning

local-aiarxiv-cs-lg

PreferThinker: Reasoning-based Personalized Image Preference Assessment

arXiv:2511.00609v4 Announce Type: replace Abstract: Personalized image preference assessment aims to evaluate an individual user's image preferences by relying only on a small set of reference images

ProMSA:Progressive Multimodal Search Agents for Knowledge-Based Visual Question Answering

arXiv:2606.27974v1 Announce Type: cross Abstract: Knowledge-based Visual Question Answering (KB-VQA) requires models to combine image understanding with external knowledge. Most prior methods use a fi

agentsarxiv-cs-ai

Quenched large deviations for Monte Carlo integration with Coulomb gases

arXiv:2508.01392v2 Announce Type: replace Abstract: Gibbs measures, such as Coulomb gases, are popular in modelling systems of interacting particles. Recently, we proposed to use Gibbs measures as ran

Tutorials

Relating Reinforcement Learning to Dynamic Programming-Based Planning

arXiv:2603.07844v2 Announce Type: replace Abstract: This paper bridges some of the gap between optimal planning and reinforcement learning (RL), both of which share roots in dynamic programming applie

tutorialsarxiv-cs-ro

Scalable and Differentiable Point-Cloud Registration Using Maximum Mean Discrepancy

arXiv:2606.27818v1 Announce Type: new Abstract: We present MMD-Reg, a novel correspondence-free approach to point-cloud registration that is differentiable and has linear computational complexity in t

safetyarxiv-cs-cv

Scene and Human in One World: Reconstruction in a Feedforward Pass

arXiv:2606.27720v1 Announce Type: new Abstract: Reconstructing humans in dynamic scenes from moving monocular cameras remains challenging due to scale ambiguity, human-scene misalignment, and occlusio

local-aiarxiv-cs-cv

Seven Security Challenges That Must be Solved in Cross-domain Multi-agent LLM Systems

arXiv:2505.23847v4 Announce Type: replace-cross Abstract: Large language models (LLMs) are rapidly evolving into autonomous agents that cooperate across organizational boundaries, enabling joint disas

SHIFT: Gate-Modulated Activation Steering for Knowledge Conflict Mitigation in Retrieval-Augmented Generation

arXiv:2606.27786v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) enhances LLMs by incorporating external knowledge to support response generation. However, conflicts between retr

STAG: Spatio-temporal Evolving Structural Representation of Action Units for Micro-expression Recognition

arXiv:2606.28083v1 Announce Type: cross Abstract: Micro-expression recognition is challenging due to subtle and short-lived facial muscle movements. Existing methods rely heavily on apex-onset frames,

TeRoR: Decoupled Temporal Rotation with Relational Circular Region for Temporal Knowledge Graph Embedding

arXiv:2606.27651v1 Announce Type: new Abstract: In recent years, with the emergence of Temporal Knowledge Graphs (TKGs), research on learning entity and relation representations in TKGs has attracted

Applications

The Minimal Search Space for Conditional Causal Bandits

arXiv:2502.06577v3 Announce Type: replace-cross Abstract: Causal knowledge can be used to support decision-making problems. This has been recognized in the causal bandits literature, where a causal (m

applicationsarxiv-cs-ai

Towards Reliable and Robust LLM Planning: Symbolic Feedback-Driven Iterative Self-Refinement Framework

arXiv:2606.27757v1 Announce Type: new Abstract: Large language models (LLMs) have attracted widespread attention from academia and industry, yet their deployment raises critical security concerns rega

Trust Region Masking for Long-Horizon LLM Reinforcement Learning

arXiv:2512.23075v5 Announce Type: replace-cross Abstract: Policy gradient methods for Large Language Models optimize a policy pi_heta via a surrogate objective computed from samples of a rollout polic

Trustworthy Predictive Distributions for Tail Events with Semiparametric Diagnostic Transport Maps

arXiv:2603.11229v2 Announce Type: replace-cross Abstract: Machine learning forecast systems are moving beyond point predictions to full predictive distributions for future outcomes y conditional on co

local-aiarxiv-cs-lg

Two-Stage Cross-Domain Cervical Abnormality Screening with Cytopathological Image Synthesis and Knowledge Distillation

arXiv:2606.27678v1 Announce Type: new Abstract: Cross-domain diagnosis remains a major challenge in cervical cell pathology due to pronounced domain shifts across institutions and the subtle visual di

safetyarxiv-cs-cv

Understanding How MLLMs Describe Artworks Using Token Activation Maps

arXiv:2606.27947v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) describe artworks with remarkable fluency, yet the visual reasoning behind their outputs remains opaque. When a

Tutorials

Web2Grasp: Learning Functional Grasps from Web Images of Hand-Object Interactions

arXiv:2505.05517v3 Announce Type: replace Abstract: Functional grasping is essential for enabling dexterous multi-finger robot hands to manipulate objects effectively. Prior work largely focuses on po

tutorialsarxiv-cs-cv

When Does Personality Composition Matter for Multi-Agent LLM Teams?

arXiv:2606.27443v1 Announce Type: new Abstract: Personality prompting shapes how large language models communicate, yet whether these behavioral shifts affect objective task outcomes remains under-exp

agentsarxiv-cs-ai

Accelerating Skill Assessment in Chess: A Drift-Diffusion-Enhanced Elo Rating System

arXiv:2606.26267v1 Announce Type: new Abstract: Rating systems such as Elo serve as the gold standard for matchmaking in competitive chess. However, they inherently suffer from response lag due to the

AlgoEvolve: LLM-driven Meta-evolution of Algorithmic Trading Programs

arXiv:2606.26173v1 Announce Type: new Abstract: Recent work shows that Large Language Models (LLMs) can act as semantic mutation operators for the evolutionary discovery of programs and proofs. Most c

agentsarxiv-cs-ai

Hardware

CARVE: Content-Aware Recurrent with Value Efficiency for Chunk-Parallel Linear Attention

arXiv:2606.27229v1 Announce Type: cross Abstract: Recurrent models must forget in order to remember, yet the state of the art decides what to erase without consulting what is stored -- the gate sees o

hardwarearxiv-cs-ai

Hardware

CAT-Q: Cost-efficient and Accurate Ternary Quantization for LLMs

arXiv:2606.26650v1 Announce Type: cross Abstract: In this paper, we present CAT-Q, Cost-efficient and Accurate Ternary Quantization, for compressing and accelerating LLMs. Unlike existing state-of-the

hardwarearxiv-cs-ai

Chisme: Heterogeneity-Aware Gossip Learning

arXiv:2505.09854v3 Announce Type: replace Abstract: As end-user device capability increases and demand for intelligent services at the Internet's edge rises, distributed learning has emerged as a key

local-aiarxiv-cs-lg

Clinical Harness for Governable Medical AI Skill Ecosystems

arXiv:2606.26494v1 Announce Type: new Abstract: Medical AI remains organized around isolated models, whereas clinical care requires accountable capabilities that persist across time. We propose clinic

Controllable Egocentric Video Generation via Occlusion-Aware Sparse 3D Hand Joints

arXiv:2603.11755v2 Announce Type: replace Abstract: Controllable video generation for complex hand-object interactions is a critical step toward building visual world models. However, existing methods

DnA: Denoising Attention for Visual Tasks

arXiv:2606.27372v1 Announce Type: new Abstract: The softmax activation in multihead attention (MHA) is the de facto standard for attention-based models in visual perception tasks. However, standard so

Applications

Dual-Prototype Disentanglement: A Context-Aware Enhancement Framework for Time Series Forecasting

arXiv:2601.16632v4 Announce Type: replace-cross Abstract: Time series forecasting has witnessed significant progress with deep learning. While prevailing approaches enhance forecasting performance by

applicationsarxiv-cs-ai