53 citations · 78 across the 19 of their papers we have counts for
20 papers
EvolvingBrain: An Adaptive Skill System for Multi-modal Agents Self-Evolution in Open Worlds
Runxuan Liu, Jingqi Shi, Baoxin Wang +10
Multi-modal agents have made significant progress in interacting with open worlds. However, their ability to self-evolve remains limited. Supervised fine-tuning enables imitation b…
CE-GOCD: Central Entity-Guided Graph Optimization for Community Detection to Augment LLM Scientific Question Answering
Jiayin Lan, Jiaqi Li, Baoxin Wang +5
Large Language Models (LLMs) are increasingly used for question answering over scientific research papers. Existing retrieval augmentation methods often rely on isolated text chunk…
Graph Reasoning Paradigm: Structured and Symbolic Reasoning with Topology-Aware Reinforcement Learning for Large Language Models
Runxuan Liu, Xianhao Ou, Xinyan Ma +13
Long Chain-of-Thought (LCoT), achieved by Reinforcement Learning with Verifiable Rewards (RLVR), has proven effective in enhancing the reasoning capabilities of Large Language Mode…
RE: Improving Chinese Grammatical Error Correction via Retrieving Appropriate Examples with Explanation
Baoxin Wang, Yumeng Luo, Yixuan Wang +3
The primary objective of Chinese grammatical error correction (CGEC) is to detect and correct errors in Chinese sentences. Recent research shows that large language models (LLMs) h…
From Hypothesis to Publication: A Comprehensive Survey of AI-Driven Research Support Systems
Zekun Zhou, Xiaocheng Feng, Lei Huang +11
Research is a fundamental process driving the advancement of human civilization, yet it demands substantial time and effort from researchers. In recent years, the rapid development…
NLP-AKG: Few-Shot Construction of NLP Academic Knowledge Graph Based on LLM
Jiayin Lan, Jiaqi Li, Baoxin Wang +4
Large language models (LLMs) have been widely applied in question answering over scientific research papers. To enhance the professionalism and accuracy of responses, many studies…
Level-Navi Agent: A Framework and benchmark for Chinese Web Search Agents
Chuanrui Hu, Shichong Xie, Baoxin Wang +3
Large language models (LLMs), adopted to understand human language, drive the development of artificial intelligence (AI) web search agents. Compared to traditional search engines,…
Ontology-Guided Reverse Thinking Makes Large Language Models Stronger on Knowledge Graph Question Answering
Runxuan Liu, Bei Luo, Jiaqi Li +5
Large language models (LLMs) have shown remarkable capabilities in natural language processing. However, in knowledge graph question answering tasks (KGQA), there remains the issue…
Improving Contextual Faithfulness of Large Language Models via Retrieval Heads-Induced Optimization
Lei Huang, Xiaocheng Feng, Weitao Ma +9
Ensuring contextual faithfulness in retrieval-augmented large language models (LLMs) is crucial for building trustworthy information-seeking systems, particularly in long-form ques…
SCITAT: A Question Answering Benchmark for Scientific Tables and Text Covering Diverse Reasoning Types
Xuanliang Zhang, Dingzirui Wang, Baoxin Wang +6
Scientific question answering (SQA) is an important task aimed at answering questions based on papers. However, current SQA datasets have limited reasoning types and neglect the re…
FLEXTAF: Enhancing Table Reasoning with Flexible Tabular Formats
Xuanliang Zhang, Dingzirui Wang, Longxu Dou +4
The table reasoning task aims to answer the question according to the given table. Currently, using Large Language Models (LLMs) is the predominant method for table reasoning. Most…
SparkRA: A Retrieval-Augmented Knowledge Service System Based on Spark Large Language Model
Dayong Wu, Jiaqi Li, Baoxin Wang +10
Large language models (LLMs) have shown remarkable achievements across various language tasks.To enhance the performance of LLMs in scientific literature services, we developed the…
Improving Grammatical Error Correction via Contextual Data Augmentation
Yixuan Wang, Baoxin Wang, Yijun Liu +3
Nowadays, data augmentation through synthetic data has been widely used in the field of Grammatical Error Correction (GEC) to alleviate the problem of data scarcity. However, these…
LM-Combiner: A Contextual Rewriting Model for Chinese Grammatical Error Correction
Yixuan Wang, Baoxin Wang, Yijun Liu +2
Over-correction is a critical problem in Chinese grammatical error correction (CGEC) task. Recent work using model ensemble methods based on voting can effectively mitigate over-co…
CSED: A Chinese Semantic Error Diagnosis Corpus
Bo Sun, Baoxin Wang, Yixuan Wang +4
Recently, much Chinese text error correction work has focused on Chinese Spelling Check (CSC) and Chinese Grammatical Error Diagnosis (CGED). In contrast, little attention has been…
Overview of CTC 2021: Chinese Text Correction for Native Speakers
Honghong Zhao, Baoxin Wang, Dayong Wu +3
In this paper, we present an overview of the CTC 2021, a Chinese text correction task for native speakers. We give detailed descriptions of the task definition and the data for tra…
Improving Pre-trained Language Models with Syntactic Dependency Prediction Task for Chinese Semantic Error Recognition
Bo Sun, Baoxin Wang, Wanxiang Che +3
Existing Chinese text error detection mainly focuses on spelling and simple grammatical errors. These errors have been studied extensively and are relatively simple for humans. On…
CINO: A Chinese Minority Pre-trained Language Model
Ziqing Yang, Zihang Xu, Yiming Cui +4
Multilingual pre-trained language models have shown impressive performance on cross-lingual tasks. It greatly facilitates the applications of natural language processing on low-res…
InterHT: Knowledge Graph Embeddings by Interaction between Head and Tail Entities
Baoxin Wang, Qingye Meng, Ziyue Wang +6
Knowledge graph embedding (KGE) models learn the representation of entities and relations in knowledge graphs. Distance-based methods show promising performance on link prediction…
CJRC: A Reliable Human-Annotated Benchmark DataSet for Chinese Judicial Reading Comprehension
Xingyi Duan, Baoxin Wang, Ziyue Wang +9
We present a Chinese judicial reading comprehension (CJRC) dataset which contains approximately 10K documents and almost 50K questions with answers. The documents come from judgmen…