update pub

_bibliography/papers.bib

@@ -218,6 +218,16 @@ @article{Dong2023StatisticalKA
   preview = {Dong2023StatisticalKA.png}
 }
 
+@article{Wang2022EvaluatingSL,
+  title   = {Evaluating Self-Supervised Learning for Molecular Graph Embeddings},
+  author  = {Hanchen Wang and Jean Kaddour and Shengchao Liu and Jian Tang and Matt J. Kusner and Joan Lasenby and Qi Liu},
+  journal = {In Advances in Neural Information Processing Systems (NeurIPS)},
+  year    = {2023},
+  volume  = {abs/2206.08005},
+  url     = {https://api.semanticscholar.org/CorpusID:249712002},
+  preview = {Wang2022EvaluatingSL.png}
+}
+
 @article{Wu2022SelfAdaptiveIL,
   title   = {Self-Adaptive In-Context Learning: An Information Compression Perspective for In-Context Example Selection and Ordering},
   author  = {Zhiyong Wu and Yaoxiang Wang and Jiacheng Ye and Lingpeng Kong},
@@ -256,6 +266,16 @@ @article{Zhao2023SORTIEDS
   preview = {Zhao2023SORTIEDS.png}
 }
 
+@article{Su2022OneEA,
+  title   = {One Embedder, Any Task: Instruction-Finetuned Text Embeddings},
+  author  = {Hongjin Su and Weijia Shi and Jungo Kasai and Yizhong Wang and Yushi Hu and Mari Ostendorf and Wen-tau Yih and Noah A. Smith and Luke Zettlemoyer and Tao Yu},
+  journal = {In Findings of the Annual Meeting of the Association for Computational Linguistics (ACL Findings)},
+  year    = {2023},
+  arxiv   = {2212.09741},
+  code    = {https://instructor-embedding.github.io/},
+  preview = {Su2022OneEA.png}
+}
+
 @article{Ye2023CompositionalEF,
   title   = {Compositional Exemplars for In-context Learning},
   author  = {Jiacheng Ye and Zhiyong Wu and Jiangtao Feng and Tao Yu and Lingpeng Kong},
@@ -276,6 +296,16 @@ @article{Zhang2022CABCA
   preview = {Zhang2022CABCA.png}
 }
 
+@article{Lai2022DS1000AN,
+  title   = {DS-1000: A Natural and Reliable Benchmark for Data Science Code Generation},
+  author  = {Yuhang Lai and Chengxi Li and Yiming Wang and Tianyi Zhang and Ruiqi Zhong and Luke Zettlemoyer and Scott Yih and Daniel Fried and Si-yi Wang and Tao Yu},
+  journal = {In Proceedings of the International Conference on Machine Learning (ICML)},
+  year    = {2023},
+  arxiv   = {2211.11501},
+  code    = {https://github.com/xlang-ai/DS-1000},
+  preview = {Lai2022DS1000AN.png}
+}
+
 @article{Zheng2023EfficientAV,
   title   = {Efficient Attention via Control Variates},
   author  = {Lin Zheng and Jianbo Yuan and Chong Wang and Lingpeng Kong},
@@ -351,6 +381,14 @@ @article{chen2023unsupervised
   preview  = {chen2023unsupervised.png}
 }
 
+@article{Wang2022AnES,
+  title   = {An Empirical Study of Retrieval-Enhanced Graph Neural Networks},
+  author  = {Dingmin Wang and Shengchao Liu and Hanchen Wang and Bernardo Cuenca Grau and Linfeng Song and Jian Tang and Song Le and Qi Li},
+  journal = {European Conference on Artificial Intelligence (ECAI)},
+  year    = {2023},
+  preview = {Wang2022AnES.png}
+}
+
 @article{ma2023retrieved,
   title   = {Retrieved Sequence Augmentation for Protein Representation Learning},
   author  = {Chang Ma and Haiteng Zhao and Lin Zheng and Jiayi Xin and Qintong Li and Lijun Wu and Zhihong Deng and Yang Lu and Qi Liu and Lingpeng Kong},
@@ -375,146 +413,125 @@ @article{zheng2023reparameterized
 %%%%%%%%%%%% 2022 %%%%%%%%%%%%
 
 
-
 @article{Ye2022ProGenPZ,
   title   = {ProGen: Progressive Zero-shot Dataset Generation via In-context Feedback},
   author  = {Jiacheng Ye and Jiahui Gao and Jiangtao Feng and Zhiyong Wu and Tao Yu and Lingpeng Kong},
   journal = {In Findings of the Conference on Empirical Methods in Natural Language Processing (EMNLP Findings)},
   year    = {2022},
   arxiv   = {2210.12329},
-  code    = {https://github.com/HKUNLP/ProGen}
-}
-
-
-@article{su2022embedder,
-  title   = {One Embedder, Any Task: Instruction-Finetuned Text Embeddings},
-  author  = {Su, Hongjin and Shi, Weijia and Kasai, Jungo and Wang, Yizhong and Hu, Yushi and Ostendorf, Mari and Yih, Wen-tau and Smith, Noah A and Zettlemoyer, Luke and Yu, Tao},
-  journal = {Preprint},
-  year    = {2022},
-  arxiv   = {2212.09741},
-  code    = {https://github.com/HKUNLP/instructor-embedding},
-  data    = {https://huggingface.co/hkunlp/instructor-large},
-  poster  = {https://instructor-embedding.github.io}
+  code    = {https://github.com/HKUNLP/ProGen},
+  preview = {Ye2022ProGenPZ.png}
 }
 
-@article{lai2022ds,
-  title    = {DS-1000: A Natural and Reliable Benchmark for Data Science Code Generation},
-  author   = {Lai, Yuhang and Li, Chengxi and Wang, Yiming and Zhang, Tianyi and Zhong, Ruiqi and Zettlemoyer, Luke and Yih, Scott Wen-tau and Fried, Daniel and Wang, Sida and Yu, Tao},
-  journal  = {Preprint},
-  year     = {2022},
-  arxiv    = {2211.11501},
-  code     = {https://github.com/HKUNLP/DS-1000},
-  poster   = {https://ds1000-code-gen.github.io/},
-  data     = {https://github.com/HKUNLP/DS-1000/tree/main/ds1000_example},
-  selected = {y}
-}
-
-
 @article{liu2022augmenting,
   title   = {Augmenting Multi-Turn Text-to-SQL Datasets with Self-Play},
   author  = {Liu, Qi and Ye, Zihuiwen and Yu, Tao and Blunsom, Phil and Song, Linfeng},
-  journal = {Findings of EMNLP 2022},
+  journal = {In Findings of the Conference on Empirical Methods in Natural Language Processing (EMNLP Findings)},
   year    = {2022},
-  note    = {Long Paper},
   arxiv   = {2210.12096},
-  code    = {https://github.com/leuchine/self_play_picard}
-}
-
-
-@article{wang2022evaluating,
-  title   = {Evaluating Self-Supervised Learning for Molecular Graph Embeddings},
-  author  = {Wang, Hanchen and Kaddour, Jean and Liu, Shengchao and Tang, Jian and Kusner, Matt and Lasenby, Joan and Liu, Qi},
-  journal = {arXiv preprint arXiv:2206.08005},
-  year    = {2022},
-  arxiv   = {2206.08005}
-}
-
-@article{wang2022augmenting,
-  title   = {Retrieval-enhanced Graph Neural Networks for Graph Property Prediction},
-  author  = {Wang, Dingmin and Liu, Shengchao and Wang, Hanchen and Song, Linfeng and Tang, Jian and Le, Song and Grau, Bernardo Cuenca and Liu, Qi},
-  journal = {arXiv preprint arXiv:2206.00362},
-  year    = {2022},
-  arxiv   = {2206.00362}
+  code    = {https://github.com/leuchine/self_play_picard},
+  preview = {liu2022augmenting.png}
 }
 
 @article{ye2022zerogen,
   title   = {ZeroGen: Efficient Zero-shot Learning via Dataset Generation},
   author  = {Ye, Jiacheng and Gao, Jiahui and Li, Qintong and Xu, Hang and Feng, Jiangtao and Wu, Zhiyong and Yu, Tao and Kong, Lingpeng},
-  journal = {Empirical Methods in Natural Language Processing (EMNLP)},
+  journal = {In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP)},
   year    = {2022},
   arxiv   = {2202.07922},
-  code    = {https://github.com/jiacheng-ye/ZeroGen}
+  code    = {https://github.com/jiacheng-ye/ZeroGen},
+  preview = {ye2022zerogen.png}
 }
 
 @article{xie2022unifiedskg,
   title   = {UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models},
   author  = {Xie, Tianbao and Wu, Chen Henry and Shi, Peng and Zhong, Ruiqi and Scholak, Torsten and Yasunaga, Michihiro and Wu, Chien-Sheng and Zhong, Ming and Yin, Pengcheng and Wang, Sida and Zhong, Victor and Wang, Bailin and Li, Chengzu and Boyle, Connor and Ni, Ansong and Yao, Ziyu and Radev, Dragomir and Xiong, Caiming and Kong, Lingpeng and Zhang, Rui and Smith, Noah A. and Zettlemoyer, Luke and Yu, Tao},
-  journal = {Empirical Methods in Natural Language Processing (EMNLP)},
+  journal = {In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP)},
   year    = {2022},
   arxiv   = {2201.05966},
   code    = {https://github.com/hkunlp/unifiedskg},
-  poster  = {https://unifiedskg.com/}
+  poster  = {https://unifiedskg.com/},
+  preview = {xie2022unifiedskg.png}
 }
 
-@article{zheng2021cascaded,
-  title   = {Cascaded Head-colliding Attention},
-  author  = {Lin Zheng and Zhiyong Wu and Lingpeng Kong},
-  journal = {Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL)},
-  year    = {2021},
-  arxiv   = {2105.14850},
-  code    = {https://github.com/LZhengisme/CODA}
-}
-
-@article{wu2021good,
-  title   = {Good for Misconceived Reasons: An Empirical Revisiting on the Need for Visual Context in Multimodal Machine Translation},
-  author  = {Zhiyong Wu and Lingpeng Kong and Wei Bi and Xiang Li and Ben Kao},
-  journal = {Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL)},
-  year    = {2021},
-  arxiv   = {2105.14462},
-  code    = {https://github.com/LividWo/Revisit-MMT}
+@article{An2022CoNTCN,
+  title   = {CoNT: Contrastive Neural Text Generation},
+  author  = {Chen An and Jiangtao Feng and Kai Lv and Lingpeng Kong and Xipeng Qiu and Xuanjing Huang},
+  journal = {In Advances in Neural Information Processing Systems (NeurIPS)},
+  year    = {2022},
+  arxiv   = {2205.14690},
+  code    = {https://github.com/Shark-NLP/CoNT},
+  preview = {An2022CoNTCN.png}
 }
 
 @article{zheng2022linear,
   title   = {Linear Complexity Randomized Self-attention Mechanism},
   author  = {Lin Zheng and Chong Wang and Lingpeng Kong},
-  journal = {Proceedings of the International Conference on Machine Learning (ICML)},
+  journal = {In Proceedings of the International Conference on Machine Learning (ICML)},
   year    = {2022},
   arxiv   = {2204.04667},
-  code    = {https://github.com/HKUNLP/efficient-attention}
+  code    = {https://github.com/HKUNLP/efficient-attention},
+  preview = {zheng2022linear.png}
 }
 
 @article{zheng2022ripple,
   title   = {Ripple Attention for Visual Perception with Sub-quadratic Complexity},
   author  = {Lin Zheng and Huijie Pan and Lingpeng Kong},
-  journal = {Proceedings of the International Conference on Machine Learning (ICML)},
-  year    = {2022},
-  arxiv   = {2110.02453}
-}
-
-@article{prange2022linguistic,
-  title   = {Linguistic Frameworks Go Toe-to-Toe at Neuro-Symbolic Language Modeling},
-  author  = {Jakob Prange and Nathan Schneider and Lingpeng Kong},
-  journal = {Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)},
+  journal = {In Proceedings of the International Conference on Machine Learning (ICML)},
   year    = {2022},
-  arxiv   = {2112.07874},
-  code    = {https://github.com/jakpra/LinguisticStructureLM}
+  arxiv   = {2110.02453},
+  preview = {zheng2022ripple.png}
 }
 
 @article{li2022event,
   title   = {Event Transition Planning for Open-ended Text Generation},
   author  = {Qintong Li and Piji Li and Wei Bi and Zhaochun Ren and Yuxuan Lai and Lingpeng Kong},
-  journal = {Findings of the Annual Meeting of the Association for Computational Linguistics (ACL Findings)},
+  journal = {In Findings of the Annual Meeting of the Association for Computational Linguistics (ACL Findings)},
   year    = {2022},
   arxiv   = {2204.09453},
-  code    = {https://github.com/qtli/EventPlanforTextGen}
+  code    = {https://github.com/qtli/EventPlanforTextGen},
+  preview = {li2022event.png}
 }
 
+
 @article{wu2022lexical,
   title   = {Lexical Knowledge Internalization for Neural Dialog Generation},
   author  = {Zhiyong Wu and Wei Bi and Xiang Li and Lingpeng Kong and Ben Kao},
-  journal = {Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL)},
+  journal = {In Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL)},
   year    = {2022},
   arxiv   = {2205.01941},
-  code    = {https://github.com/LividWo/KI}
+  code    = {https://github.com/LividWo/KI},
+  preview = {wu2022lexical.png}
 }
 
+@inproceedings{Prange2021LinguisticFG,
+  title     = {Linguistic Frameworks Go Toe-to-Toe at Neuro-Symbolic Language Modeling},
+  author    = {Jakob Prange and Nathan Schneider and Lingpeng Kong},
+  booktitle = {North American Chapter of the Association for Computational Linguistics (NAACL)},
+  year      = {2022},
+  arxiv     = {2112.07874},
+  preview   = {wu2022lexical.png}
+}
+
+
+%%%%%%%%%%%% 2021 %%%%%%%%%%%%%%%%%%%
+
+@article{zheng2021cascaded,
+  title   = {Cascaded Head-colliding Attention},
+  author  = {Lin Zheng and Zhiyong Wu and Lingpeng Kong},
+  journal = {In Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL)},
+  year    = {2021},
+  arxiv   = {2105.14850},
+  code    = {https://github.com/LZhengisme/CODA},
+  preview = {zheng2021cascaded.png}
+}
+
+@article{wu2021good,
+  title   = {Good for Misconceived Reasons: An Empirical Revisiting on the Need for Visual Context in Multimodal Machine Translation},
+  author  = {Zhiyong Wu and Lingpeng Kong and Wei Bi and Xiang Li and Ben Kao},
+  journal = {In Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL)},
+  year    = {2021},
+  arxiv   = {2105.14462},
+  code    = {https://github.com/LividWo/Revisit-MMT},
+  preview = {wu2021good.png}
+}