Last Updated: @2023/10/14
长期研究目标:在AI系统中,引入人类视角的信息,以构建更强大的AI系统以及更优雅的人机交互范式。
目录 Content
- 目录 Content
- 会议论文 Conference Papers
- StructLM: Towards Building Generalist Models for Structured Knowledge Grounding
- CMMMU: A Chinese Massive Multi-discipline Multimodal Understanding Benchmark
- [SIGIR-AP 2023] EALM: Introducing Multidimensional Ethical Alignment in Conversational Information Retrieval
- [ACL 2023] UniEX: An Effective and Efficient Framework for Unified Information Extraction via a Span-extractive Perspective
- [ACL 2023] Solving Math Word Problems via Cooperative Reasoning induced Language Models
- NER-to-MRC: Named-Entity Recognition Completely Solving as Machine Reading Comprehension
- [CVPR 2023] MAP: Modality-Agnostic Uncertainty-Aware Vision-Language Pre-training Model
- [EMNLP 2022] Zero-Shot Learners for Natural Language Understanding via a Unified Multiple Choice Perspective
- [ACM MM 2022] Breaking Isolation: Multimodal Graph Fusion for Multimedia Recommendation by Edge-wise Modulation
- Fengshenbang 1.0: Being the Foundation of Chinese Cognitive Intelligence
- Towards No.1 in CLUE Semantic Matching Challenge: Pre-trained Language Model Erlangshen with Propensity-Corrected Loss
- [EMNLP 2021] MIRTT: Learning Multimodal Interaction Representations from Trilinear Transformers for Visual Question Answering
- [NTCIR 15] SKYMN at the NTCIR-15 DialEval-1 Task
- 期刊论文 Journal Papers
- [ACM TOIS 2024] SSR: Solving Named Entity Recognition Problems via a Single-stream Reasoner
会议论文 Conference Papers
StructLM: Towards Building Generalist Models for Structured Knowledge Grounding
- Arxiv https://arxiv.org/abs/2402.16671
- Structured knowlegde grounding, LLM, unified format, multiple sources
- Update @2024/02/27
CMMMU: A Chinese Massive Multi-discipline Multimodal Understanding Benchmark
- Arxiv https://arxiv.org/abs/2401.11944
- Multimodal understanding, chinese, evaluation
- Update @2024/01/22
[SIGIR-AP 2023] EALM: Introducing Multidimensional Ethical Alignment in Conversational Information Retrieval
- ArXiv https://arxiv.org/abs/2310.00970
- Human ethics, multidimensional ethical alignment
- Update: @2023/09/10
[ACL 2023] UniEX: An Effective and Efficient Framework for Unified Information Extraction via a Span-extractive Perspective
- ACL 2023 https://aclanthology.org/2023.acl-long.907/
- ArXiv https://arxiv.org/abs/2210.16257
- Information extraction, unified framework, zero-shot, few-shot, finetuning, multitaak learning
- Update: @2023/06/18
[ACL 2023] Solving Math Word Problems via Cooperative Reasoning induced Language Models
- ACL 2023 https://aclanthology.org/2023.acl-long.245/
- ArXiv https://arxiv.org/abs/2210.16257
- Reasoning, math problems, language models, improving LMs
- Update: @2023/05/04
NER-to-MRC: Named-Entity Recognition Completely Solving as Machine Reading Comprehension
- ArXiv https://arxiv.org/abs/2305.03970
- Named-Entiry Recognition, Machine reading comprehension, Reasoning, Unified tasks
- Update: @2023/05/06
[CVPR 2023] MAP: Modality-Agnostic Uncertainty-Aware Vision-Language Pre-training Model
- CVPR 2023 https://openaccess.thecvf.com/content/CVPR2023/html/Ji_MAP_Multimodal_Uncertainty-Aware_Vision-Language_Pre-Training_Model_CVPR_2023_paper.html
- ArXiv https://arxiv.org/abs/2210.05335
- Multimodal, Multimodal Pre-training, Distribution Representation, Vision-Language Downstream tasks
- Update: @2022/10/21
[EMNLP 2022] Zero-Shot Learners for Natural Language Understanding via a Unified Multiple Choice Perspective
- EMNLP 2022 https://aclanthology.org/2022.emnlp-main.474/
- ArXiv https://arxiv.org/abs/2210.08590
- NLP, Zero-shot, NLU, Unified Format
- Update: @2022/10/24
[ACM MM 2022] Breaking Isolation: Multimodal Graph Fusion for Multimedia Recommendation by Edge-wise Modulation
- ACM MM 2022 https://dl.acm.org/doi/abs/10.1145/3503161.3548399
- Multimedia, Multimodal Recommendation, Multimodal Graph. Fusion
- Update: @2022/10/10
Fengshenbang 1.0: Being the Foundation of Chinese Cognitive Intelligence
- ArXiv https://arxiv.org/abs/2209.02970
- NLP, Pre-trained Language Models, Deep Learning Framework, Benchmark, Chinese
- Update: @2022/09/07
Towards No.1 in CLUE Semantic Matching Challenge: Pre-trained Language Model Erlangshen with Propensity-Corrected Loss
- ArXiv https://arxiv.org/abs/2208.02959
- NLP, Semantic Matching, Sentence Similarity, Propensity-Corrected Loss, CLUE
[EMNLP 2021] MIRTT: Learning Multimodal Interaction Representations from Trilinear Transformers for Visual Question Answering
- EMNLP 2021 https://aclanthology.org/2021.findings-emnlp.196/
- Multimodal interaction, VQA, trilinear transformers
- Update: @2021/10/07
[NTCIR 15] SKYMN at the NTCIR-15 DialEval-1 Task
- NTCIR 15 http://research.nii.ac.jp/ntcir/workshop/OnlineProceedings15/pdf/ntcir/03-NTCIR15-DIALEVAL-WangJ.pdf
- NLP, Dialogue Evaluation, Multiple Models, Label-based Training
- Update: @2020/12/08
期刊论文 Journal Papers
[ACM TOIS 2024] SSR: Solving Named Entity Recognition Problems via a Single-stream Reasoner
- ACM TOIS 2024 https://dl.acm.org/doi/10.1145/3655619
- Information Extraction, Named Entity Recognition, Human behaviors
- Update: @2024/04/15