100 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Peking UniversityCN5 papers
- University of Chinese Academy of SciencesCN4 papers
- Chinese Academy of SciencesCN3 papers
- SP Technology (South Korea)KR3 papers
- Centre National de la Recherche ScientifiqueFR2 papers
- Institute of Applied Physics and Computational MathematicsCN2 papers
- Princeton UniversityUS2 papers
- Sorbonne UniversitéFR2 papers
- Stanford UniversityUS2 papers
- University of Science and Technology of ChinaCN2 papers
- AIRI - Artificial Intelligence Research InstituteRU1 paper
- Alpha Omega Alpha Medical Honor SocietyUS1 paper
23 papers
Prior Knowledge or Search? A Study of LLM Agents in Hardware-Aware Code Optimization
Dmitry Redko, Albert Fazlyev, Konstantin Sozykin +3
LLM discovery and optimization systems are increasingly applied across domains, implementing a common propose-evaluate-revise loop. Such optimization or discovery progresses via co…
Semantic State Abstraction Interfaces for LLM-Augmented Portfolio Decisions: Multi-Axis News Decomposition and RL Diagnostics
Likhita Yerra, Remi Uttejitha Allam
We introduce Semantic State Abstraction Interfaces (SSAI): a methodological template for mapping sparse unstructured text into auditable, named coordinates with neutral default…
Human Motion Video Generation: A Survey
Haiwei Xue, Xiangyang Luo, Zhanghao Hu +12
Human motion video generation has garnered significant research interest due to its broad applications, enabling innovations such as photorealistic singing heads or dynamic avatars…
RTD-Lite: Scalable Topological Analysis for Comparing Weighted Graphs in Learning Tasks
Eduard Tulchinskii, Daria Voronkova, Ilya Trofimov +2
Topological methods for comparing weighted graphs are valuable in various learning tasks but often suffer from computational inefficiency on large datasets. We introduce RTD-Lite,…
DeePMD-kit v3: A Multiple-Backend Framework for Machine Learning Potentials
Jinzhe Zeng, Duo Zhang, Anyang Peng +44
In recent years, machine learning potentials (MLPs) have become indispensable tools in physics, chemistry, and materials science, driving the development of software packages for m…
Deep variational free energy prediction of dense hydrogen solid at 1200K
Xinyang Dong, Hao Xie, Yixiao Chen +4
We perform deep variational free energy calculations to investigate the dense hydrogen system at 1200 K and high pressures. In this computational framework, neural networks are use…
Exploring the energy landscape of aluminas through machine learning interatomic potential
Lei Zhang, Wenhao Luo, Renxi Liu +3
Aluminum oxide (alumina, AlO) exists in various structures and has broad industrial applications. While the crystal structure of -AlO is well-established, those…
LEGATO: Cross-Embodiment Imitation Using a Grasping Tool
Mingyo Seo, H. Andy Park, Shenli Yuan +2
Cross-embodiment imitation learning enables policies trained on specific embodiments to transfer across different robots, unlocking the potential for large-scale imitation learning…
Solvation Free Energies from Neural Thermodynamic Integration
Bálint Máté, François Fleuret, Tristan Bereau
We present a method for computing free-energy differences using thermodynamic integration with a neural network potential that interpolates between two target Hamiltonians. The int…
Prospector Heads: Generalized Feature Attribution for Large Models & Data
Gautam Machiraju, Alexander Derry, Arjun Desai +6
Feature attribution, the ability to localize regions of the input data that are relevant for classification, is an important capability for ML models in scientific and biomedical d…
Bridge Diffusion Model: Bridge Chinese Text-to-Image Diffusion Model with English Communities
Shanyuan Liu, Bo Cheng, Yuhang Ma +5
Text-to-Image generation (TTI) technologies are advancing rapidly, especially in the English language communities. However, apart from the user input language barrier problem, Engl…
Machine Reading Comprehension using Case-based Reasoning
Dung Thai, Dhruv Agarwal, Mudit Chaudhary +6
We present an accurate and interpretable method for answer extraction in machine reading comprehension that is reminiscent of case-based reasoning (CBR) from classical AI. Our meth…
The Elephant in the Room: Analyzing the Presence of Big Tech in Natural Language Processing Research
Mohamed Abdalla, Jan Philip Wahle, Terry Ruas +4
Recent advances in deep learning methods for natural language processing (NLP) have created new business opportunities and made NLP research critical for industry development. As o…
Computational exploration of a viable route to Kitaev-quantum spin liquid phase in OsCl
Qiangqiang Gu, Shishir Kumar Pandey, Yihao Lin
In this computational study, we explore a viable route to access the Kitaev-Quantum Spin Liquid (QSL) state in recently synthesized monolayer of a so-called spin-orbit assisted Mot…
Reaching Through Latent Space: From Joint Statistics to Path Planning in Manipulation
Chia-Man Hung, Shaohong Zhong, Walter Goodwin +4
We present a novel approach to path planning for robotic manipulators, in which paths are produced via iterative optimisation in the latent space of a generative model of robot pos…
Progressive Optimal Path Sampling for Closed-Loop Optimal Control Design with Deep Neural Networks
Xuanxi Zhang, Jihao Long, Wei Hu +2
Closed-loop optimal control design for high-dimensional nonlinear systems has been a long-standing challenge. Traditional methods, such as solving the associated Hamilton-Jacobi-Be…
Affective Signals in a Social Media Recommender System
Jane Dwivedi-Yu, Yi-Chia Wang, Lijing Qin +2
People come to social media to satisfy a variety of needs, such as being informed, entertained and inspired, or connected to their friends and community. Hence, to design a ranking…
VSA: Reconfigurable Vectorwise Spiking Neural Network Accelerator
Hong-Han Lien, Chung-Wei Hsu, Tian-Sheuan Chang
Spiking neural networks (SNNs) that enable low-power design on edge devices have recently attracted significant research. However, the temporal characteristic of SNNs causes high l…
Prescriptive and Descriptive Approaches to Machine-Learning Transparency
David Adkins, Bilal Alsallakh, Adeel Cheema +7
Specialized documentation techniques have been developed to communicate key facts about machine-learning (ML) systems and the datasets and models they rely on. Techniques such as D…
Transformer Inertial Poser: Real-time Human Motion Reconstruction from Sparse IMUs with Simultaneous Terrain Generation
Yifeng Jiang, Yuting Ye, Deepak Gopinath +3
Real-time human motion reconstruction from a sparse set of (e.g. six) wearable IMUs provides a non-intrusive and economic approach to motion capture. Without the ability to acquire…
of two-dimensional electron gas: a neural canonical transformation study
Hao Xie, Linfeng Zhang, Lei Wang
The quasiparticle effective mass of interacting electrons is a fundamental quantity in the Fermi liquid theory. However, the precise value of the effective mass of uniform…
Referring Image Segmentation via Cross-Modal Progressive Comprehension
Shaofei Huang, Tianrui Hui, Si Liu +5
Referring image segmentation aims at segmenting the foreground masks of the entities that can well match the description given in the natural language expression. Previous approach…
Nonconvex Sparse Spectral Clustering by Alternating Direction Method of Multipliers and Its Convergence Analysis
Canyi Lu, Jiashi Feng, Zhouchen Lin +1
Spectral Clustering (SC) is a widely used data clustering method which first learns a low-dimensional embedding of data by computing the eigenvectors of the normalized Laplacia…