Search Results for author: Zhicheng Yang

Found 20 papers, 10 papers with code

Are LLMs Really Not Knowledgable? Mining the Submerged Knowledge in LLMs' Memory

no code implementations30 Dec 2024 Xingjian Tao, Yiwei Wang, Yujun Cai, Zhicheng Yang, Jing Tang

Large language models (LLMs) have shown promise as potential knowledge bases, yet they often struggle with question-answering tasks and are prone to hallucinations.

Question Answering

CityWalker: Learning Embodied Urban Navigation from Web-Scale Videos

1 code implementation26 Nov 2024 Xinhao Liu, Jintong Li, Yicheng Jiang, Niranjan Sujay, Zhicheng Yang, Juexiao Zhang, John Abanes, Jing Zhang, Chen Feng

This work shows the potential of using abundant online video data to develop robust navigation policies for embodied agents in dynamic urban settings.

Common Sense Reasoning Imitation Learning +2

ZALM3: Zero-Shot Enhancement of Vision-Language Alignment via In-Context Information in Multi-Turn Multimodal Medical Dialogue

no code implementations26 Sep 2024 Zhangpu Li, Changhong Zou, Suxue Ma, Zhicheng Yang, Chen Du, YouBao Tang, Zhenjie Cao, Ning Zhang, Jui-Hsin Lai, Ruei-Sung Lin, Yuan Ni, Xingzhi Sun, Jing Xiao, Jieke Hou, Kai Zhang, Mei Han

In our online medical consultation scenario, a doctor responds to the texts and images provided by a patient in multiple rounds to diagnose her/his health condition, forming a multi-turn multimodal medical dialogue format.

Medical Visual Question Answering Question Answering +2

OptiBench Meets ReSocratic: Measure and Improve LLMs for Optimization Modeling

1 code implementation13 Jul 2024 Zhicheng Yang, Yiwei Wang, Yinya Huang, Zhijiang Guo, Wei Shi, Xiongwei Han, Liang Feng, Linqi Song, Xiaodan Liang, Jing Tang

Furthermore, to alleviate the data scarcity for optimization problems, and to bridge the gap between open-source LLMs on a small scale (e. g., Llama-3-8b) and closed-source LLMs (e. g., GPT-4), we further propose a data synthesis method namely ReSocratic.

Benchmarking Math +1

Process-Driven Autoformalization in Lean 4

2 code implementations4 Jun 2024 Jianqiao Lu, Yingjia Wan, Zhengying Liu, Yinya Huang, Jing Xiong, Chengwu Liu, Jianhao Shen, Hui Jin, Jipeng Zhang, Haiming Wang, Zhicheng Yang, Jing Tang, Zhijiang Guo

Autoformalization, the conversion of natural language mathematics into formal languages, offers significant potential for advancing mathematical reasoning.

Mathematical Reasoning

Proving Theorems Recursively

1 code implementation23 May 2024 Haiming Wang, Huajian Xin, Zhengying Liu, Wenda Li, Yinya Huang, Jianqiao Lu, Zhicheng Yang, Jing Tang, Jian Yin, Zhenguo Li, Xiaodan Liang

This approach allows the theorem to be tackled incrementally by outlining the overall theorem at the first level and then solving the intermediate conjectures at deeper levels.

Automated Theorem Proving

ATG: Benchmarking Automated Theorem Generation for Generative Language Models

no code implementations5 May 2024 Xiaohan Lin, Qingxing Cao, Yinya Huang, Zhicheng Yang, Zhengying Liu, Zhenguo Li, Xiaodan Liang

We conduct extensive experiments to investigate whether current LMs can generate theorems in the library and benefit the problem theorems proving.

Automated Theorem Proving Benchmarking

AlignedCoT: Prompting Large Language Models via Native-Speaking Demonstrations

1 code implementation22 Nov 2023 Zhicheng Yang, Yinya Huang, Jing Xiong, Liang Feng, Xiaodan Liang, Yiwei Wang, Jing Tang

Large Language Models prompting, such as using in-context demonstrations, is a mainstream technique for invoking LLMs to perform high-performance and solid complex reasoning (e. g., mathematical reasoning, commonsense reasoning), and has the potential for further human-machine collaborative scientific findings.

Common Sense Reasoning GSM8K +4

DQ-LoRe: Dual Queries with Low Rank Approximation Re-ranking for In-Context Learning

1 code implementation4 Oct 2023 Jing Xiong, Zixuan Li, Chuanyang Zheng, Zhijiang Guo, Yichun Yin, Enze Xie, Zhicheng Yang, Qingxing Cao, Haiming Wang, Xiongwei Han, Jing Tang, Chengming Li, Xiaodan Liang

Dual Queries first query LLM to obtain LLM-generated knowledge such as CoT, then query the retriever to obtain the final exemplars via both question and the knowledge.

Dimensionality Reduction In-Context Learning +1

Agriculture-Vision Challenge 2022 -- The Runner-Up Solution for Agricultural Pattern Recognition via Transformer-based Models

no code implementations23 Jun 2022 Zhicheng Yang, Jui-Hsin Lai, Jun Zhou, Hang Zhou, Chen Du, Zhongcheng Lai

The Agriculture-Vision Challenge in CVPR is one of the most famous and competitive challenges for global researchers to break the boundary between computer vision and agriculture sectors, aiming at agricultural pattern recognition from aerial images.

Data Augmentation

Unbiased Math Word Problems Benchmark for Mitigating Solving Bias

2 code implementations Findings (NAACL) 2022 Zhicheng Yang, Jinghui Qin, Jiaqi Chen, Xiaodan Liang

However, current solvers exist solving bias which consists of data bias and learning bias due to biased dataset and improper training strategy.

Math

LogicSolver: Towards Interpretable Math Word Problem Solving with Logical Prompt-enhanced Learning

2 code implementations17 May 2022 Zhicheng Yang, Jinghui Qin, Jiaqi Chen, Liang Lin, Xiaodan Liang

To address this issue and make a step towards interpretable MWP solving, we first construct a high-quality MWP dataset named InterMWP which consists of 11, 495 MWPs and annotates interpretable logical formulas based on algebraic knowledge as the grounded linguistic logic of each solution equation.

Math Math Word Problem Solving

Leveraging Large-Scale Weakly Labeled Data for Semi-Supervised Mass Detection in Mammograms

no code implementations CVPR 2021 Yuxing Tang, Zhenjie Cao, Yanbo Zhang, Zhicheng Yang, Zongcheng Ji, Yiwei Wang, Mei Han, Jie Ma, Jing Xiao, Peng Chang

Starting with a fully supervised model trained on the data with pixel-level masks, the proposed framework iteratively refines the model itself using the entire weakly labeled data (image-level soft label) in a self-training fashion.

Prior Guided Feature Enrichment Network for Few-Shot Segmentation

3 code implementations4 Aug 2020 Zhuotao Tian, Hengshuang Zhao, Michelle Shu, Zhicheng Yang, Ruiyu Li, Jiaya Jia

It consists of novel designs of (1) a training-free prior mask generation method that not only retains generalization power but also improves model performance and (2) Feature Enrichment Module (FEM) that overcomes spatial inconsistency by adaptively enriching query features with support features and prior masks.

Few-Shot Semantic Segmentation Semantic Segmentation

2D Attentional Irregular Scene Text Recognizer

no code implementations13 Jun 2019 Pengyuan Lyu, Zhicheng Yang, Xinhang Leng, Xiao-Jun Wu, Ruiyu Li, Xiaoyong Shen

Irregular scene text, which has complex layout in 2D space, is challenging to most previous scene text recognizers.

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