Papers
Research papers from arXiv and related sources
Deep Clustering based Boundary-Decoder Net for Inter and Intra Layer Stress Prediction of Heterogeneous Integrated IC Chip
High stress occurs when 3D heterogeneous IC packages are subjected to thermal cycling at extreme temperatures. Stress mainly occurs at the interface between different materials. We investigate stre...
Kart Leong Lim, Ji Lin
AQR-HNSW: Accelerating Approximate Nearest Neighbor Search via Density-aware Quantization and Multi-stage Re-ranking
Approximate Nearest Neighbor (ANN) search has become fundamental to modern AI infrastructure, powering recommendation systems, search engines, and large language models across industry leaders from...
Ganap Ashit Tewary, Nrusinga Charan Gantayat, Jeff Zhang
Iterative Closed-Loop Motion Synthesis for Scaling the Capabilities of Humanoid Control
Physics-based humanoid control relies on training with motion datasets that have diverse data distributions. However, the fixed difficulty distribution of datasets limits the performance ceiling of...
Weisheng Xu, Qiwei Wu, Jiaxi Zhang, Tan Jing, Yangfan Li, Yuetong Fang, Jiaqi Xiong, Kai Wu, Rong...
Retrieval Challenges in Low-Resource Public Service Information: A Case Study on Food Pantry Access
Public service information systems are often fragmented, inconsistently formatted, and outdated. These characteristics create low-resource retrieval environments that hinder timely access to critic...
Touseef Hasan, Laila Cure, Souvika Sarkar
SPOC: Safety-Aware Planning Under Partial Observability And Physical Constraints
Embodied Task Planning with large language models faces safety challenges in real-world environments, where partial observability and physical constraints must be respected. Existing benchmarks oft...
Hyungmin Kim, Hobeom Jeon, Dohyung Kim, Minsu Jang, Jeahong Kim
Breaking Semantic-Aware Watermarks via LLM-Guided Coherence-Preserving Semantic Injection
Generative images have proliferated on Web platforms in social media and online copyright distribution scenarios, and semantic watermarking has increasingly been integrated into diffusion models to...
Zheng Gao, Xiaoyu Li, Zhicheng Bao, Xiaoyan Feng, Jiaojiao Jiang
CADC: Content Adaptive Diffusion-Based Generative Image Compression
Diffusion-based generative image compression has demonstrated remarkable potential for achieving realistic reconstruction at ultra-low bitrates. The key to unlocking this potential lies in making t...
Xihua Sheng, Lingyu Zhu, Tianyu Zhang, Dong Liu, Shiqi Wang, Jing Wang
Physics Informed Neural Network using Finite Difference Method
In recent engineering applications using deep learning, physics-informed neural network (PINN) is a new development as it can exploit the underlying physics of engineering systems. The novelty of P...
Kart Leong Lim, Rahul Dutta, Mihai Rotaru
Hall effect on nontrivial quadrupole order in quasi-kagome compound URhSn
This study focuses on the transport properties of the quasi-kagome compound URhSn, which exhibits successive phase transitions at TC =16 K (ferromagnetic phase) and TO =54 K (intermediate phase). A...
Yusei Shimizu, Arvind Maurya, Yoshiya Homma, Motoi Kimata, Toni Helm, Ai Nakamura, Dexin Li, Atsu...
Duel-Evolve: Reward-Free Test-Time Scaling via LLM Self-Preferences
Many applications seek to optimize LLM outputs at test time by iteratively proposing, scoring, and refining candidates over a discrete output space. Existing methods use a calibrated scalar evaluat...
Sweta Karlekar, Carolina Zheng, Magnus Saebo, Nicolas Beltran-Velez, Shuyang Yu, John Bowlan, Mic...
Exploring Human-Machine Coexistence in Symmetrical Reality
In the context of the evolution of artificial intelligence (AI), the interaction between humans and AI entities has become increasingly salient, challenging the conventional human-centric paradigms...
Zhenliang Zhang
Goodness-of-Fit Tests for Latent Class Models with Ordinal Categorical Data
Ordinal categorical data are widely collected in psychology, education, and other social sciences, appearing commonly in questionnaires, assessments, and surveys. Latent class models provide a flex...
Huan Qing
How many asymmetric communities are there in multi-layer directed networks?
Estimating the asymmetric numbers of communities in multi-layer directed networks is a challenging problem due to the multi-layer structures and inherent directional asymmetry, leading to possibly ...
Huan Qing
Power and Limitations of Aggregation in Compound AI Systems
When designing compound AI systems, a common approach is to query multiple copies of the same model and aggregate the responses to produce a synthesized output. Given the homogeneity of these model...
Nivasini Ananthakrishnan, Meena Jagadeesan
DualPath: Breaking the Storage Bandwidth Bottleneck in Agentic LLM Inference
The performance of multi-turn, agentic LLM inference is increasingly dominated by KV-Cache storage I/O rather than computation. In prevalent disaggregated architectures, loading the massive KV-Cach...
Yongtong Wu, Shaoyuan Chen, Yinmin Zhong, Rilin Huang, Yixuan Tan, Wentao Zhang, Liyue Zhang, Sha...
RAC: Relation-Aware Cache Replacement for Large Language Models
The scaling of Large Language Model (LLM) services faces significant cost and latency challenges, making effective caching under tight capacity crucial. Existing cache replacement policies, from he...
Yuchong Wu, Zihuan Xu, Wangze Ni, Peng Cheng, Lei Chen, Xuemin Lin, Heng Tao Shen, Kui Ren
ARLArena: A Unified Framework for Stable Agentic Reinforcement Learning
Agentic reinforcement learning (ARL) has rapidly gained attention as a promising paradigm for training agents to solve complex, multi-step interactive tasks. Despite encouraging early results, ARL ...
Xiaoxuan Wang, Han Zhang, Haixin Wang, Yidan Shi, Ruoyan Li, Kaiqiao Han, Chenyi Tong, Haoran Den...
Reasoning-Driven Design of Single Atom Catalysts via a Multi-Agent Large Language Model Framework
Large language models (LLMs) are becoming increasingly applied beyond natural language processing, demonstrating strong capabilities in complex scientific tasks that traditionally require human exp...
Dong Hyeon Mok, Seoin Back, Victor Fung, Guoxiang Hu
Elastic neutrino-electron scattering perspectives at nuclear reactors
The determination of the weak mixing angle, $\sin^2θ_W$, at low momentum transfers remains a powerful test of the Standard Model and its potential new physics extensions. In this paper, we explore ...
Luis A. Delgadillo, Qishan Liu, Randhir Singh
One Brain, Omni Modalities: Towards Unified Non-Invasive Brain Decoding with Large Language Models
Deciphering brain function through non-invasive recordings requires synthesizing complementary high-frequency electromagnetic (EEG/MEG) and low-frequency metabolic (fMRI) signals. However, despite ...
Changli Tang, Shurui Li, Junliang Wang, Qinfan Xiao, Zhonghao Zhai, Lei Bai, Yu Qiao, Bowen Zhou,...