most citedChain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding

12 citations · 18 across the 6 of their papers we have counts for

collaborators

6 papers

physics.geo-ph20241 cited

Parts-per-billion Trace Element Detection in Anhydrous Minerals by Micro-scale Quantitative NMR

Yunhua Fu, Renbiao Tao, Lifei Zhang +5

Nominally anhydrous minerals (NAMs) composing Earth's and planetary rocks incorporate microscopic amounts of volatiles. However, volatile distribution in NAMs and their effect on p…

cs.CL20245 cited

LLM-RadJudge: Achieving Radiologist-Level Evaluation for X-Ray Report Generation

Zilong Wang, Xufang Luo, Xinyang Jiang +2

Evaluating generated radiology reports is crucial for the development of radiology AI, but existing metrics fail to reflect the task's clinical requirements. This study proposes a…

cs.CL2024

DOCMASTER: A Unified Platform for Annotation, Training, & Inference in Document Question-Answering

Alex Nguyen, Zilong Wang, Jingbo Shang +1

The application of natural language processing models to PDF documents is pivotal for various business applications yet the challenge of training models for this purpose persists i…

cs.CL202412 cited

Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding

Zilong Wang, Hao Zhang, Chun-Liang Li +8

Table-based reasoning with large language models (LLMs) is a promising direction to tackle many table understanding tasks, such as table-based question answering and fact verificat…

q-bio.NC2023

A Computational Model of Children's Learning and Use of Probabilities Across Different Ages

Zilong Wang, Thomas R. Shultz, Ardvan S. Nobandegani

Recent empirical work has shown that human children are adept at learning and reasoning with probabilities. Here, we model a recent experiment investigating the development of scho…

cs.CR2023

Improved Differential-neural Cryptanalysis for Round-reduced Simeck32/64

Liu Zhang, Jinyu Lu, Zilong Wang +1

In CRYPTO 2019, Gohr presented differential-neural cryptanalysis by building the differential distinguisher with a neural network, achieving practical 11-, and 12-round key recover…