Search: “models”

From Prediction to Justification: Aligning Sentiment Reasoning with Human Rationale via Reinforcement Learning

arXiv:2604.13398v1 Announce Type: new Abstract: While Aspect-based Sentiment Analysis (ABSA) systems have achieved high accuracy in identifying sentiment polarities, they often operate as 'black boxes

researcharxiv-cs-cl

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Research

Frozen Forecasting: A Unified Evaluation

DGX agent

arXiv:2507.13942v2 Announce Type: replace Abstract: Forecasting future events is a fundamental capability for general-purpose systems that plan or act across different levels of abstraction. Yet, eval

researcharxiv-cs-cv

16 Apr 2026

HINTBench: Horizon-agent Intrinsic Non-attack Trajectory Benchmark

arXiv:2604.13954v1 Announce Type: new Abstract: Existing agent-safety evaluation has focused mainly on externally induced risks. Yet agents may still enter unsafe trajectories under benign conditions.

Irregularly Sampled Time Series Interpolation for Binary Evolution Simulations Using Dynamic Time Warping

arXiv:2604.13604v1 Announce Type: cross Abstract: Binary stellar evolution simulations are computationally expensive. Stellar population synthesis relies on these detailed evolution models at a fundam

safetyarxiv-cs-lg

Jump-Start Reinforcement Learning with Vision-Language-Action Regularization

arXiv:2604.13733v1 Announce Type: new Abstract: Reinforcement learning (RL) enables high-frequency, closed-loop control for robotic manipulation, but scaling to long-horizon tasks with sparse or imper

safetyarxiv-cs-lg

Agents

Memp: Exploring Agent Procedural Memory

arXiv:2508.06433v4 Announce Type: replace Abstract: Large Language Models (LLMs) based agents excel at diverse tasks, yet they suffer from brittle procedural memory that is manually engineered or enta

agentsarxiv-cs-cl

Tutorials

Optimizing Earth Observation Satellite Schedules under Unknown Operational Constraints: An Active Constraint Acquisition Approach

arXiv:2604.13283v1 Announce Type: cross Abstract: Earth Observation (EO) satellite scheduling (deciding which imaging tasks to perform and when) is a well-studied combinatorial optimization problem. E

tutorialsarxiv-cs-lg

Pareto-Optimal Offline Reinforcement Learning via Smooth Tchebysheff Scalarization

arXiv:2604.13175v1 Announce Type: new Abstract: Large language models can be aligned with human preferences through offline reinforcement learning (RL) on small labeled datasets. While single-objectiv

safetyarxiv-cs-lg

Tutorials

PartNerFace: Part-based Neural Radiance Fields for Animatable Facial Avatar Reconstruction

arXiv:2604.13918v1 Announce Type: new Abstract: We present PartNerFace, a part-based neural radiance fields approach, for reconstructing animatable facial avatar from monocular RGB videos. Existing so

tutorialsarxiv-cs-cv

PatchPoison: Poisoning Multi-View Datasets to Degrade 3D Reconstruction

arXiv:2604.13153v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has recently enabled highly photorealistic 3D reconstruction from casually captured multi-view images. However, this access

Quantum Machine Learning for Colorectal Cancer Data: Anastomotic Leak Classification and Risk Factors

arXiv:2604.13951v1 Announce Type: new Abstract: This study evaluates colorectal risk factors and compares classical models against Quantum Neural Networks (QNNs) for anastomotic leak prediction. Analy

RANDPOL: Parameter-Efficient End-to-End Quadruped Locomotion via Randomized Policy Learning

arXiv:2505.19054v2 Announce Type: replace Abstract: Modern learning-based locomotion controllers typically rely on fully trainable deep neural networks with a large number of parameters. This paper st

Reconstruction of a 3D wireframe from a single line drawing via generative depth estimation

arXiv:2604.13549v1 Announce Type: new Abstract: The conversion of 2D freehand sketches into 3D models remains a pivotal challenge in computer vision, bridging the gap between human creativity and digi

Local Ai

Rethinking Image-to-3D Generation with Sparse Queries: Efficiency, Capacity, and Input-View Bias

arXiv:2604.13905v1 Announce Type: new Abstract: We present SparseGen, a novel framework for efficient image-to-3D generation, which exhibits low input-view bias while being significantly faster. Unlik

local-aiarxiv-cs-cv

SemAttNet: Towards Attention-based Semantic Aware Guided Depth Completion

arXiv:2204.13635v2 Announce Type: replace Abstract: Depth completion involves recovering a dense depth map from a sparse map and an RGB image. Recent approaches focus on utilizing color images as guid

SHARe-KAN: Post-Training Vector Quantization for Cache-Resident KAN Inference

arXiv:2512.15742v2 Announce Type: replace Abstract: Pre-trained Vision Kolmogorov-Arnold Networks (KANs) store a dense B-spline grid on every edge, inflating prediction-head parameter counts by more t

SocialMirror: Reconstructing 3D Human Interaction Behaviors from Monocular Videos with Semantic and Geometric Guidance

arXiv:2604.13581v1 Announce Type: new Abstract: Accurately reconstructing human behavior in close-interaction scenarios is crucial for enabling realistic virtual interactions in augmented reality, pre

Synthesis and Deployment of Maximal Robust Control Barrier Functions through Adversarial Reinforcement Learning

model-releasesarxiv-cs-ro

arXiv:2604.13192v1 Announce Type: cross Abstract: Robust control barrier functions (CBFs) provide a principled mechanism for smooth safety enforcement under worst-case disturbances. However, existing

Synthetic Tabular Generators Fail to Preserve Behavioral Fraud Patterns: A Benchmark on Temporal, Velocity, and Multi-Account Signals

arXiv:2604.13125v1 Announce Type: new Abstract: We introduce behavioral fidelity -- a third evaluation dimension for synthetic tabular data that measures whether generated data preserves the temporal,

Text-as-Signal: Quantitative Semantic Scoring with Embeddings, Logprobs, and Noise Reduction

model-releasesarxiv-cs-cl

arXiv:2604.13056v1 Announce Type: new Abstract: This paper presents a practical pipeline for turning text corpora into quantitative semantic signals. Each news item is represented as a full-document e

The Gaussian Latent Machine: Efficient Prior and Posterior Sampling for Inverse Problems

arXiv:2505.12836v2 Announce Type: replace-cross Abstract: We consider the problem of sampling from a product-of-experts-type model that encompasses many standard prior and posterior distributions comm

TIP: Token Importance in On-Policy Distillation

arXiv:2604.14084v1 Announce Type: new Abstract: On-policy knowledge distillation (OPD) trains a student on its own rollouts under token-level supervision from a teacher. Not all token positions matter

Towards Unconstrained Human-Object Interaction

arXiv:2604.14069v1 Announce Type: new Abstract: Human-Object Interaction (HOI) detection is a longstanding computer vision problem concerned with predicting the interaction between humans and objects.

Two Pathways to Truthfulness: On the Intrinsic Encoding of LLM Hallucinations

arXiv:2601.07422v2 Announce Type: replace Abstract: Despite their impressive capabilities, large language models (LLMs) frequently generate hallucinations. Previous work shows that their internal stat

researcharxiv-cs-cl

UI-Copilot: Advancing Long-Horizon GUI Automation via Tool-Integrated Policy Optimization

arXiv:2604.13822v1 Announce Type: new Abstract: MLLM-based GUI agents have demonstrated strong capabilities in complex user interface interaction tasks. However, long-horizon scenarios remain challeng

VIGILant: an automatic classification pipeline for glitches in the Virgo detector

arXiv:2604.13687v1 Announce Type: cross Abstract: Glitches frequently contaminate data in gravitational-wave detectors, complicating the observation and analysis of astrophysical signals. This work in

WIN-U: Woodbury-Informed Newton-Unlearning as a retain-free Machine Unlearning Framework

arXiv:2604.13438v1 Announce Type: new Abstract: Privacy concerns in LLMs have led to the rapidly growing need to enforce a data's 'right to be forgotten'. Machine unlearning addresses precisely this t

YOCO++: Enhancing YOCO with KV Residual Connections for Efficient LLM Inference

arXiv:2604.13556v1 Announce Type: new Abstract: Cross-layer key-value (KV) compression has been found to be effective in efficient inference of large language models (LLMs). Although they reduce the m

researcharxiv-cs-cl

Zero-Shot Function Encoder-Based Differentiable Predictive Control

arXiv:2511.05757v3 Announce Type: replace-cross Abstract: We introduce a differentiable framework for zero-shot adaptive control over parametric families of nonlinear dynamical systems. Our approach i

A Layer-wise Analysis of Supervised Fine-Tuning

model-releasesarxiv-cs-ai

arXiv:2604.11838v1 Announce Type: cross Abstract: While critical for alignment, Supervised Fine-Tuning (SFT) incurs the risk of catastrophic forgetting, yet the layer-wise emergence of instruction-fol

Adaptive Data Dropout: Towards Self-Regulated Learning in Deep Neural Networks

arXiv:2604.12945v1 Announce Type: cross Abstract: Deep neural networks are typically trained by uniformly sampling large datasets across epochs, despite evidence that not all samples contribute equall

Agents

AgenticAI-DialogGen: Topic-Guided Conversation Generation for Fine-Tuning and Evaluating Short- and Long-Term Memories of LLMs

arXiv:2604.12179v1 Announce Type: new Abstract: Recent advancements in Large Language Models (LLMs) have improved their ability to process extended conversational contexts, yet fine-tuning and evaluat

agentsarxiv-cs-cl

Applications

All in One: A Unified Synthetic Data Pipeline for Multimodal Video Understanding

arXiv:2604.12335v1 Announce Type: new Abstract: Training multimodal large language models (MLLMs) for video understanding requires large-scale annotated data spanning diverse tasks such as object coun

applicationsarxiv-cs-cv

ART-VITON: Measurement-Guided Latent Diffusion for Artifact-Free Virtual Try-On

arXiv:2509.25749v2 Announce Type: cross Abstract: Virtual try-on (VITON) aims to generate realistic images of a person wearing a target garment, requiring precise garment alignment in try-on regions a

safetyarxiv-cs-ai

BEAM: Bi-level Memory-adaptive Algorithmic Evolution for LLM-Powered Heuristic Design

arXiv:2604.12898v1 Announce Type: new Abstract: Large Language Model-based Hyper Heuristic (LHH) has recently emerged as an efficient way for automatic heuristic design. However, most existing LHHs ju

researcharxiv-cs-ai

Beyond Single-Dimension Novelty: How Combinations of Theory, Method, and Results-based Novelty Shape Scientific Impact

model-releasesarxiv-cs-cl

arXiv:2604.12471v1 Announce Type: cross Abstract: Scientific novelty drives advances at the research frontier, yet it is also associated with heightened uncertainty and potential resistance from incum

BRAIN: Bias-Mitigation Continual Learning Approach to Vision-Brain Understanding

arXiv:2508.18187v2 Announce Type: replace-cross Abstract: Memory decay makes it harder for the human brain to recognize visual objects and retain details. Consequently, recorded brain signals become w

safetyarxiv-cs-ai

Bridging the Micro--Macro Gap: Frequency-Aware Semantic Alignment for Image Manipulation Localization

arXiv:2604.12341v1 Announce Type: new Abstract: As generative image editing advances, image manipulation localization (IML) must handle both traditional manipulations with conspicuous forensic artifac

safetyarxiv-cs-cv

CamReasoner: Reinforcing Camera Movement Understanding via Structured Spatial Reasoning

arXiv:2602.00181v3 Announce Type: replace-cross Abstract: Understanding camera dynamics is a fundamental pillar of video spatial intelligence. However, existing multimodal models predominantly treat t

safetyarxiv-cs-ai

Applications

ChemDFM-R: A Chemical Reasoning LLM Enhanced with Atomized Chemical Knowledge

arXiv:2507.21990v4 Announce Type: replace-cross Abstract: Atomized chemical knowledge, such as functional group information of molecules and reactions, plays a pivotal intermediate role in the reasoni

applicationsarxiv-cs-ai

Classification of Epileptic iEEG using Topological Machine Learning

arXiv:2604.11971v1 Announce Type: new Abstract: Epileptic seizure detection from EEG signals remains challenging due to the high dimensionality and nonlinear, potentially stochastic, dynamics of neura

Clustering-Enhanced Domain Adaptation for Cross-Domain Intrusion Detection in Industrial Control Systems

model-releasesarxiv-cs-ai

arXiv:2604.12183v1 Announce Type: cross Abstract: Industrial control systems operate in dynamic environments where traffic distributions vary across scenarios, labeled samples are limited, and unknown

Complementarity by Construction: A Lie-Group Approach to Solving Quadratic Programs with Linear Complementarity Constraints

model-releasesarxiv-cs-ro

arXiv:2604.11991v1 Announce Type: new Abstract: Many problems in robotics require reasoning over a mix of continuous dynamics and discrete events, such as making and breaking contact in manipulation a

Curvelet-Based Frequency-Aware Feature Enhancement for Deepfake Detection

arXiv:2604.12028v1 Announce Type: cross Abstract: The proliferation of sophisticated generative models has significantly advanced the realism of synthetic facial content, known as deepfakes, raising s

researcharxiv-cs-ai

DC-TTA: Divide-and-Conquer Framework for Test-Time Adaptation of Interactive Segmentation

arXiv:2506.23104v2 Announce Type: replace Abstract: Interactive segmentation (IS) allows users to iteratively refine object boundaries with minimal cues, such as positive and negative clicks. While th

DecompSR: A dataset for decomposed analyses of compositional multihop spatial reasoning

model-releasesarxiv-cs-ai

arXiv:2511.02627v2 Announce Type: replace Abstract: We introduce DecompSR, decomposed spatial reasoning, a large benchmark dataset (over 5m datapoints) and generation framework designed to analyse com

DeCoNav: Dialog enhanced Long-Horizon Collaborative Vision-Language Navigation

model-releasesarxiv-cs-ro

arXiv:2604.12486v1 Announce Type: new Abstract: Long-horizon collaborative vision-language navigation (VLN) is critical for multi-robot systems to accomplish complex tasks beyond the capability of a s

DeferredSeg: A Multi-Expert Deferral Framework for Trustworthy Medical Image Segmentation

arXiv:2604.12411v1 Announce Type: new Abstract: Segmentation models based on deep neural networks demonstrate strong generalization for medical image segmentation. However, they often exhibit overconf