Search: “model-releases”

Hypergraph Neural Diffusion: A PDE-Inspired Framework for Hypergraph Message Passing

arXiv:2604.10955v1 Announce Type: new Abstract: Hypergraph neural networks (HGNNs) have shown remarkable potential in modeling high-order relationships that naturally arise in many real-world data dom

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Model Releases

I Can't Believe TTA Is Not Better: When Test-Time Augmentation Hurts Medical Image Classification

DGX agent

arXiv:2604.09697v1 Announce Type: cross Abstract: Test-time augmentation (TTA)--aggregating predictions over multiple augmented copies of a test input--is widely assumed to improve classification accu

model-releasesarxiv-cs-ai

14 Apr 2026

Identifying Inductive Biases for Robot Co-Design

model-releasesarxiv-cs-ro

arXiv:2604.11768v1 Announce Type: new Abstract: Co-designing a robot's morphology and control can ensure synergistic interactions between them, prevalent in biological organisms. However, co-design is

If an LLM Were a Character, Would It Know Its Own Story? Evaluating Lifelong Learning in LLMs

arXiv:2503.23514v2 Announce Type: replace-cross Abstract: Large language models (LLMs) can carry out human-like dialogue, but unlike humans, they are stateless due to the superposition property. Howev

Immunizing 3D Gaussian Generative Models Against Unauthorized Fine-Tuning via Attribute-Space Traps

arXiv:2604.09688v1 Announce Type: new Abstract: Recent large-scale generative models enable high-quality 3D synthesis. However, the public accessibility of pre-trained weights introduces a critical vu

IMPACT: A Dataset for Multi-Granularity Human Procedural Action Understanding in Industrial Assembly

arXiv:2604.10409v1 Announce Type: cross Abstract: We introduce IMPACT, a synchronized five-view RGB-D dataset for deployment-oriented industrial procedural understanding, built around real assembly an

Incentivizing Honesty among Competitors in Collaborative Learning and Optimization

arXiv:2305.16272v5 Announce Type: replace Abstract: Collaborative learning techniques have the potential to enable training machine learning models that are superior to models trained on a single enti

Infusing Theory of Mind into Socially Intelligent LLM Agents

arXiv:2509.22887v2 Announce Type: replace Abstract: Theory of Mind (ToM)-an understanding of the mental states of others-is a key aspect of human social intelligence, yet, chatbots and LLM-based socia

INSPATIO-WORLD: A Real-Time 4D World Simulator via Spatiotemporal Autoregressive Modeling

arXiv:2604.07209v2 Announce Type: replace Abstract: Building world models with spatial consistency and real-time interactivity remains a fundamental challenge in computer vision. Current video generat

Integrating Semi-Supervised and Active Learning for Semantic Segmentation

arXiv:2501.19227v2 Announce Type: replace-cross Abstract: In this paper, we propose a novel active learning approach integrated with an improved semi-supervised learning framework to reduce the cost o

Intent-aligned Formal Specification Synthesis via Traceable Refinement

arXiv:2604.10392v1 Announce Type: cross Abstract: Large language models are increasingly used to generate code from natural language, but ensuring correctness remains challenging. Formal verification

Intersectional Sycophancy: How Perceived User Demographics Shape False Validation in Large Language Models

arXiv:2604.11609v1 Announce Type: new Abstract: Large language models exhibit sycophantic tendencies--validating incorrect user beliefs to appear agreeable. We investigate whether this behavior varies

Investigating Bias and Fairness in Appearance-based Gaze Estimation

arXiv:2604.10707v1 Announce Type: new Abstract: While appearance-based gaze estimation has achieved significant improvements in accuracy and domain adaptation, the fairness of these systems across dif

Investigating Vaccine Buyer's Remorse: Post-Vaccination Decision Regret in COVID-19 Social Media Using Politically Diverse Human Annotation

arXiv:2604.09626v1 Announce Type: cross Abstract: A significant gap exists in datasets regarding post-COVID-19 vaccination experiences, particularly ``vaccine buyer's remorse''. Understanding the prev

Is There Knowledge Left to Extract? Evidence of Fragility in Medically Fine-Tuned Vision-Language Models

arXiv:2604.09841v1 Announce Type: cross Abstract: Vision-language models (VLMs) are increasingly adapted through domain-specific fine-tuning, yet it remains unclear whether this improves reasoning bey

ITIScore: An Image-to-Text-to-Image Rating Framework for the Image Captioning Ability of MLLMs

arXiv:2604.03765v2 Announce Type: replace Abstract: Recent advances in multimodal large language models (MLLMs) have greatly improved image understanding and captioning capabilities. However, existing

K-Way Energy Probes for Metacognition Reduce to Softmax in Discriminative Predictive Coding Networks

arXiv:2604.11011v1 Announce Type: cross Abstract: We present this as a negative result with an explanatory mechanism, not as a formal upper bound. Predictive coding networks (PCNs) admit a K-way energ

Knowing What to Stress: A Discourse-Conditioned Text-to-Speech Benchmark

arXiv:2604.10580v1 Announce Type: new Abstract: Spoken meaning often depends not only on what is said, but also on which word is emphasized. The same sentence can convey correction, contrast, or clari

Knowledge Integration in Differentiable Models: A Comparative Study of Data-Driven, Soft-Constrained, and Hard-Constrained Paradigms for Identification and Control of the Single Machine Infinite Bus System

arXiv:2602.09667v2 Announce Type: replace Abstract: Integrating domain knowledge into neural networks is a central challenge in scientific machine learning. Three paradigms have emerged -- data-driven

ks-pret-5m: a 5 million word, 12 million token kashmiri pretraining dataset

arXiv:2604.11066v1 Announce Type: new Abstract: We present KS-PRET-5M, the largest publicly available pretraining dataset for the Kashmiri language, comprising 5,090,244 (5.09M) words, 27,692,959 (27.

LABBench2: An Improved Benchmark for AI Systems Performing Biology Research

arXiv:2604.09554v1 Announce Type: new Abstract: Optimism for accelerating scientific discovery with AI continues to grow. Current applications of AI in scientific research range from training dedicate

LaMI: Augmenting Large Language Models via Late Multi-Image Fusion

arXiv:2406.13621v2 Announce Type: replace Abstract: Commonsense reasoning often requires both textual and visual knowledge, yet Large Language Models (LLMs) trained solely on text lack visual groundin

Language Prompt vs. Image Enhancement: Boosting Object Detection With CLIP in Hazy Environments

arXiv:2604.10637v1 Announce Type: new Abstract: Object detection in hazy environments is challenging because degraded objects are nearly invisible and their semantics are weakened by environmental noi

Large Language Models Can Help Mitigate Barren Plateaus in Quantum Neural Networks

arXiv:2502.13166v3 Announce Type: replace-cross Abstract: In the era of noisy intermediate-scale quantum (NISQ) computing, Quantum Neural Networks (QNNs) have emerged as a promising approach for vario

LARY: A Latent Action Representation Yielding Benchmark for Generalizable Vision-to-Action Alignment

arXiv:2604.11689v1 Announce Type: new Abstract: While the shortage of explicit action data limits Vision-Language-Action (VLA) models, human action videos offer a scalable yet unlabeled data source. A

LAST: Leveraging Tools as Hints to Enhance Spatial Reasoning for Multimodal Large Language Models

arXiv:2604.09712v1 Announce Type: cross Abstract: Spatial reasoning is a cornerstone capability for intelligent systems to perceive and interact with the physical world. However, multimodal large lang

LEADER: Learning Reliable Local-to-Global Correspondences for LiDAR Relocalization

arXiv:2604.11355v1 Announce Type: new Abstract: LiDAR relocalization has attracted increasing attention as it can deliver accurate 6-DoF pose estimation in complex 3D environments. Recent learning-bas

Learning Racket-Ball Bounce Dynamics Across Diverse Rubbers for Robotic Table Tennis

model-releasesarxiv-cs-ro

arXiv:2604.11349v1 Announce Type: new Abstract: Accurate dynamic models for racket-ball bounces are essential for reliable control in robotic table tennis. Existing models typically assume simple line

Learning Robustness at Test-Time from a Non-Robust Teacher

arXiv:2604.11590v1 Announce Type: new Abstract: Nowadays, pretrained models are increasingly used as general-purpose backbones and adapted at test-time to downstream environments where target data are

Learning to Adapt: In-Context Learning Beyond Stationarity

arXiv:2604.10946v1 Announce Type: new Abstract: Transformer models have become foundational across a wide range of scientific and engineering domains due to their strong empirical performance. A key c

Learning to Play Piano in the Real World

arXiv:2503.15481v3 Announce Type: replace-cross Abstract: Towards the grand challenge of achieving human-level manipulation in robots, playing piano is a compelling testbed that requires strategic, pr

Learning What's Real: Disentangling Signal and Measurement Artifacts in Multi-Sensor Data, with Applications to Astrophysics

arXiv:2604.09787v1 Announce Type: cross Abstract: Data collected from the physical world is always a combination of multiple sources: an underlying signal from the physical process of interest and a s

Learning World Models for Interactive Video Generation

arXiv:2505.21996v3 Announce Type: replace-cross Abstract: Foundational world models must be both interactive and preserve spatiotemporal coherence for effective future planning with action choices. Ho

LIDARLearn: A Unified Deep Learning Library for 3D Point Cloud Classification, Segmentation, and Self-Supervised Representation Learning

arXiv:2604.10780v1 Announce Type: new Abstract: Three-dimensional (3D) point cloud analysis has become central to applications ranging from autonomous driving and robotics to forestry and ecological m

LIFT: A Novel Framework for Enhancing Long-Context Understanding of LLMs via Long Input Fine-Tuning

arXiv:2502.14644v5 Announce Type: replace Abstract: Long context understanding remains challenging for large language models due to their limited context windows. This paper introduces Long Input Fine

LiveCLKTBench: Towards Reliable Evaluation of Cross-Lingual Knowledge Transfer in Multilingual LLMs

arXiv:2511.14774v3 Announce Type: replace-cross Abstract: Evaluating cross-lingual knowledge transfer in large language models is challenging, as correct answers in a target language may arise either

LLMs for Text-Based Exploration and Navigation Under Partial Observability

arXiv:2604.09604v1 Announce Type: new Abstract: Exploration and goal-directed navigation in unknown layouts are central to inspection, logistics, and search-and-rescue. We ask whether large language m

LLMs Should Incorporate Explicit Mechanisms for Human Empathy

arXiv:2604.10557v1 Announce Type: cross Abstract: This paper argues that Large Language Models (LLMs) should incorporate explicit mechanisms for human empathy. As LLMs become increasingly deployed in

LoGo-MR: Screening Breast MRI for Cancer Risk Prediction by Efficient Omni-Slice Modeling

arXiv:2604.11348v1 Announce Type: new Abstract: Efficient and explainable breast cancer (BC) risk prediction is critical for large-scale population-based screening. Breast MRI provides functional info

LookBench: A Live and Holistic Open Benchmark for Fashion Image Retrieval

arXiv:2601.14706v3 Announce Type: replace Abstract: In this paper, we present LookBench (We use the term 'look' to reflect retrieval that mirrors how people shop -- finding the exact item, a close sub

LoopGuard: Breaking Self-Reinforcing Attention Loops via Dynamic KV Cache Intervention

arXiv:2604.10044v1 Announce Type: new Abstract: Through systematic experiments on long-context generation, we observe a damaging failure mode in which decoding can collapse into persistent repetition

LottieGPT: Tokenizing Vector Animation for Autoregressive Generation

arXiv:2604.11792v1 Announce Type: new Abstract: Despite rapid progress in video generation, existing models are incapable of producing vector animation, a dominant and highly expressive form of multim

LoViF 2026 Challenge on Human-oriented Semantic Image Quality Assessment: Methods and Results

arXiv:2604.11207v1 Announce Type: new Abstract: This paper reviews the LoViF 2026 Challenge on Human-oriented Semantic Image Quality Assessment. This challenge aims to raise a new direction, i.e., how

Low-rank Optimization Trajectories Modeling for LLM RLVR Acceleration

arXiv:2604.11446v1 Announce Type: cross Abstract: Recently, scaling reinforcement learning with verifiable rewards (RLVR) for large language models (LLMs) has emerged as an effective training paradigm

LRD-Net: A Lightweight Real-Centered Detection Network for Cross-Domain Face Forgery Detection

arXiv:2604.10862v1 Announce Type: new Abstract: The rapid advancement of diffusion-based generative models has made face forgery detection a critical challenge in digital forensics. Current detection

LumiMotion: Improving Gaussian Relighting with Scene Dynamics

arXiv:2604.10994v1 Announce Type: new Abstract: In 3D reconstruction, the problem of inverse rendering, namely recovering the illumination of the scene and the material properties, is fundamental. Exi

LVSum: A Benchmark for Timestamp-Aware Long Video Summarization

arXiv:2604.10024v1 Announce Type: cross Abstract: Long video summarization presents significant challenges for current multimodal large language models (MLLMs), particularly in maintaining temporal fi

M2-Verify: A Large-Scale Multidomain Benchmark for Checking Multimodal Claim Consistency

arXiv:2604.01306v2 Announce Type: replace Abstract: Evaluating scientific arguments requires assessing the strict consistency between a claim and its underlying multimodal evidence. However, existing