activity
20222025
most citedMonolith: Real Time Recommendation System With Collisionless Embedding Table

19 citations · 23 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL2025

REAP: Enhancing RAG with Recursive Evaluation and Adaptive Planning for Multi-Hop Question Answering

Yijie Zhu, Haojie Zhou, Wanting Hong +2

Retrieval-augmented generation (RAG) has been extensively employed to mitigate hallucinations in large language models (LLMs). However, existing methods for multi-hop reasoning tas…

cs.CV2025

CoEmoGen: Towards Semantically-Coherent and Scalable Emotional Image Content Generation

Kaishen Yuan, Yuting Zhang, Shang Gao +3

Emotional Image Content Generation (EICG) aims to generate semantically clear and emotionally faithful images based on given emotion categories, with broad application prospects. W…

cs.CR2025

M-ary Precomputation-Based Accelerated Scalar Multiplication Algorithms for Enhanced Elliptic Curve Cryptography

Tongxi Wu, Xufeng Liu, Jin Yang +3

Efficient scalar multiplication is critical for enhancing the performance of elliptic curve cryptography (ECC), especially in applications requiring large-scale or real-time crypto…

cs.CL2023★ 2 cited

GPT-Fathom: Benchmarking Large Language Models to Decipher the Evolutionary Path towards GPT-4 and Beyond

Shen Zheng, Yuyu Zhang, Yijie Zhu +4

With the rapid advancement of large language models (LLMs), there is a pressing need for a comprehensive evaluation suite to assess their capabilities and limitations. Existing LLM…

cs.IR2022★ 19 cited

Monolith: Real Time Recommendation System With Collisionless Embedding Table

Zhuoran Liu, Leqi Zou, Xuan Zou +8

Building a scalable and real-time recommendation system is vital for many businesses driven by time-sensitive customer feedback, such as short-videos ranking or online ads. Despite…

cs.LG2022★ 2 cited

CowClip: Reducing CTR Prediction Model Training Time from 12 hours to 10 minutes on 1 GPU

Zangwei Zheng, Pengtai Xu, Xuan Zou +12

The click-through rate (CTR) prediction task is to predict whether a user will click on the recommended item. As mind-boggling amounts of data are produced online daily, accelerati…