102 citations · 133 across the 11 of their papers we have counts for
13 papers
NarrativeSteward: Coordinating Delegation, Guidance, and Verification in Agent-Assisted Interactive Narrative Authoring
Wenjin Wang, Jiazhen Lei, Yuxin Sha +6
Autonomous AI agents can turn authors' goals into interactive narratives by independently organizing and carrying out generation and revision. As agents generate and revise extensi…
DAAF: From Failure Localization to Editable System Assets in LLM Agents
Xiaoyang Yuan, Qi Liu, Yubin Ruan +9
Deployed LLM agents increasingly rely on persistent, versioned system assets such as routing rules, knowledge segments, prompt instructions, and reusable skills. Failure-localizati…
OIG-Bench: A Multi-Agent Annotated Benchmark for Multimodal One-Image Guides Understanding
Jiancong Xie, Wenjin Wang, Zhuomeng Zhang +5
Recent advances in Multimodal Large Language Models (MLLMs) have demonstrated impressive capabilities. However, evaluating their capacity for human-like understanding in One-Image…
: Language Modeling with Explicit Memory
Hongkang Yang, Zehao Lin, Wenjin Wang +13
The training and inference of large language models (LLMs) are together a costly process that transports knowledge from raw data to meaningful computation. Inspired by the memory h…
Grimoire is All You Need for Enhancing Large Language Models
Ding Chen, Shichao Song, Qingchen Yu +4
In-context Learning (ICL) is one of the key methods for enhancing the performance of large language models on specific tasks by providing a set of few-shot examples. However, the I…
CRUD-RAG: A Comprehensive Chinese Benchmark for Retrieval-Augmented Generation of Large Language Models
Yuanjie Lyu, Zhiyu Li, Simin Niu +7
Retrieval-Augmented Generation (RAG) is a technique that enhances the capabilities of large language models (LLMs) by incorporating external knowledge sources. This method addresse…
Layout and Task Aware Instruction Prompt for Zero-shot Document Image Question Answering
Wenjin Wang, Yunhao Li, Yixin Ou +1
Layout-aware pre-trained models has achieved significant progress on document image question answering. They introduce extra learnable modules into existing language models to capt…
Task Difficulty Aware Parameter Allocation & Regularization for Lifelong Learning
Wenjin Wang, Yunqing Hu, Qianglong Chen +1
Parameter regularization or allocation methods are effective in overcoming catastrophic forgetting in lifelong learning. However, they solve all tasks in a sequence uniformly and i…
ERNIE-Layout: Layout Knowledge Enhanced Pre-training for Visually-rich Document Understanding
Qiming Peng, Yinxu Pan, Wenjin Wang +12
Recent years have witnessed the rise and success of pre-training techniques in visually-rich document understanding. However, most existing methods lack the systematic mining and u…
ERNIE-mmLayout: Multi-grained MultiModal Transformer for Document Understanding
Wenjin Wang, Zhengjie Huang, Bin Luo +8
Recent efforts of multimodal Transformers have improved Visually Rich Document Understanding (VrDU) tasks via incorporating visual and textual information. However, existing approa…
LiteGEM: Lite Geometry Enhanced Molecular Representation Learning for Quantum Property Prediction
Shanzhuo Zhang, Lihang Liu, Sheng Gao +6
In this report, we (SuperHelix team) present our solution to KDD Cup 2021-PCQM4M-LSC, a large-scale quantum chemistry dataset on predicting HOMO-LUMO gap of molecules. Our solution…
Masked Label Prediction: Unified Message Passing Model for Semi-Supervised Classification
Yunsheng Shi, Zhengjie Huang, Shikun Feng +3
Graph neural network (GNN) and label propagation algorithm (LPA) are both message passing algorithms, which have achieved superior performance in semi-supervised classification. GN…
Lifelong Learning with Searchable Extension Units
Wenjin Wang, Yunqing Hu, Yin Zhang
Lifelong learning remains an open problem. One of its main difficulties is catastrophic forgetting. Many dynamic expansion approaches have been proposed to address this problem, bu…