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Zhijing Jin 0001
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- affiliation: Max Planck Institute for Intelligent Systems, Tübingen, Germany
- affiliation: ETH Zürich, Switzerland
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2020 – today
- 2024
- [c32]Flavio Schneider, Ojasv Kamal, Zhijing Jin, Bernhard Schölkopf:
Moûsai: Efficient Text-to-Music Diffusion Models. ACL (1) 2024: 8050-8068 - [c31]Ishan Agrawal, Zhijing Jin, Ehsan Mokhtarian, Siyuan Guo, Yuen Chen, Mrinmaya Sachan, Bernhard Schölkopf:
CausalCite: A Causal Formulation of Paper Citations. ACL (Findings) 2024: 8395-8410 - [c30]Francesco Ortu, Zhijing Jin, Diego Doimo, Mrinmaya Sachan, Alberto Cazzaniga, Bernhard Schölkopf:
Competition of Mechanisms: Tracing How Language Models Handle Facts and Counterfactuals. ACL (1) 2024: 8420-8436 - [c29]Oana Ignat, Zhijing Jin, Artem Abzaliev, Laura Biester, Santiago Castro, Naihao Deng, Xinyi Gao, Aylin Gunal, Jacky He, Ashkan Kazemi, Muhammad Khalifa, Namho Koh, Andrew Lee, Siyang Liu, Do June Min, Shinka Mori, Joan Nwatu, Verónica Pérez-Rosas, Siqi Shen, Zekun Wang, Winston Wu, Rada Mihalcea:
Has It All Been Solved? Open NLP Research Questions Not Solved by Large Language Models. LREC/COLING 2024: 8050-8094 - [c28]Zhiheng Lyu, Zhijing Jin, Fernando Gonzalez Adauto, Rada Mihalcea, Bernhard Schölkopf, Mrinmaya Sachan:
Do LLMs Think Fast and Slow? A Causal Study on Sentiment Analysis. EMNLP (Findings) 2024: 9353-9372 - [c27]Zhijing Jin, Nils Heil, Jiarui Liu, Shehzaad Dhuliawala, Yahang Qi, Bernhard Schölkopf, Rada Mihalcea, Mrinmaya Sachan:
Implicit Personalization in Language Models: A Systematic Study. EMNLP (Findings) 2024: 12309-12325 - [c26]Shaobo Cui, Zhijing Jin, Bernhard Schölkopf, Boi Faltings:
The Odyssey of Commonsense Causality: From Foundational Benchmarks to Cutting-Edge Reasoning. EMNLP 2024: 16722-16763 - [c25]Zhijing Jin, Jiarui Liu, Zhiheng Lyu, Spencer Poff, Mrinmaya Sachan, Rada Mihalcea, Mona T. Diab, Bernhard Schölkopf:
Can Large Language Models Infer Causation from Correlation? ICLR 2024 - [c24]Jiarui Liu, Wenkai Li, Zhijing Jin, Mona T. Diab:
Automatic Generation of Model and Data Cards: A Step Towards Responsible AI. NAACL-HLT 2024: 1975-1997 - [c23]Zhijing Jin, Yuen Chen, Fernando Gonzalez Adauto, Jiarui Liu, Jiayi Zhang, Julian Michael, Bernhard Schölkopf, Mona T. Diab:
Analyzing the Role of Semantic Representations in the Era of Large Language Models. NAACL-HLT 2024: 3781-3798 - [i50]Francesco Ortu, Zhijing Jin, Diego Doimo, Mrinmaya Sachan, Alberto Cazzaniga, Bernhard Schölkopf:
Competition of Mechanisms: Tracing How Language Models Handle Facts and Counterfactuals. CoRR abs/2402.11655 (2024) - [i49]Charvi Rastogi, Xiangchen Song, Zhijing Jin, Ivan Stelmakh, Hal Daumé III, Kun Zhang, Nihar B. Shah:
A Randomized Controlled Trial on Anonymizing Reviewers to Each Other in Peer Review Discussions. CoRR abs/2403.01015 (2024) - [i48]Zhiheng Lyu, Zhijing Jin, Fernando Gonzalez, Rada Mihalcea, Bernhard Schölkopf, Mrinmaya Sachan:
On the Causal Nature of Sentiment Analysis. CoRR abs/2404.11055 (2024) - [i47]Giorgio Piatti, Zhijing Jin, Max Kleiman-Weiner, Bernhard Schölkopf, Mrinmaya Sachan, Rada Mihalcea:
Cooperate or Collapse: Emergence of Sustainability Behaviors in a Society of LLM Agents. CoRR abs/2404.16698 (2024) - [i46]Zhijing Jin, Yuen Chen, Fernando Gonzalez, Jiarui Liu, Jiayi Zhang, Julian Michael, Bernhard Schölkopf, Mona T. Diab:
Analyzing the Role of Semantic Representations in the Era of Large Language Models. CoRR abs/2405.01502 (2024) - [i45]Abhinav Lalwani, Lovish Chopra, Christopher Hahn, Caroline Trippel, Zhijing Jin, Mrinmaya Sachan:
NL2FOL: Translating Natural Language to First-Order Logic for Logical Fallacy Detection. CoRR abs/2405.02318 (2024) - [i44]Jiarui Liu, Wenkai Li, Zhijing Jin, Mona T. Diab:
Automatic Generation of Model and Data Cards: A Step Towards Responsible AI. CoRR abs/2405.06258 (2024) - [i43]Zhijing Jin, Nils Heil, Jiarui Liu, Shehzaad Dhuliawala, Yahang Qi, Bernhard Schölkopf, Rada Mihalcea, Mrinmaya Sachan:
Implicit Personalization in Language Models: A Systematic Study. CoRR abs/2405.14808 (2024) - [i42]Roberto Ceraolo, Dmitrii Kharlapenko, Amélie Reymond, Rada Mihalcea, Mrinmaya Sachan, Bernhard Schölkopf, Zhijing Jin:
CausalQuest: Collecting Natural Causal Questions for AI Agents. CoRR abs/2405.20318 (2024) - [i41]Robin Chan, Reda Boumasmoud, Anej Svete, Yuxin Ren, Qipeng Guo, Zhijing Jin, Shauli Ravfogel, Mrinmaya Sachan, Bernhard Schölkopf, Mennatallah El-Assady, Ryan Cotterell:
On Affine Homotopy between Language Encoders. CoRR abs/2406.02329 (2024) - [i40]Shaobo Cui, Zhijing Jin, Bernhard Schölkopf, Boi Faltings:
The Odyssey of Commonsense Causality: From Foundational Benchmarks to Cutting-Edge Reasoning. CoRR abs/2406.19307 (2024) - [i39]Zhijing Jin, Sydney Levine, Max Kleiman-Weiner, Giorgio Piatti, Jiarui Liu, Fernando Gonzalez Adauto, Francesco Ortu, András Strausz, Mrinmaya Sachan, Rada Mihalcea, Yejin Choi, Bernhard Schölkopf:
Multilingual Trolley Problems for Language Models. CoRR abs/2407.02273 (2024) - [i38]Rada Mihalcea, Oana Ignat, Longju Bai, Angana Borah, Luis Chiruzzo, Zhijing Jin, Claude Kwizera, Joan Nwatu, Soujanya Poria, Thamar Solorio:
Why AI Is WEIRD and Should Not Be This Way: Towards AI For Everyone, With Everyone, By Everyone. CoRR abs/2410.16315 (2024) - 2023
- [j2]Dieuwke Hupkes, Mario Giulianelli
, Verna Dankers, Mikel Artetxe, Yanai Elazar, Tiago Pimentel
A taxonomy and review of generalization research in NLP. Nat. Mac. Intell. 5(10): 1161-1174 (2023) - [c22]Alessandro Stolfo, Zhijing Jin, Kumar Shridhar, Bernhard Schölkopf, Mrinmaya Sachan:
A Causal Framework to Quantify the Robustness of Mathematical Reasoning with Language Models. ACL (1) 2023: 545-561 - [c21]Ping Yu, Tianlu Wang, Olga Golovneva, Badr AlKhamissi, Siddharth Verma, Zhijing Jin, Gargi Ghosh, Mona T. Diab, Asli Celikyilmaz:
ALERT: Adapt Language Models to Reasoning Tasks. ACL (1) 2023: 1055-1081 - [c20]Jingwei Ni, Zhijing Jin, Qian Wang, Mrinmaya Sachan, Markus Leippold:
When Does Aggregating Multiple Skills with Multi-Task Learning Work? A Case Study in Financial NLP. ACL (1) 2023: 7465-7488 - [c19]Justus Mattern, Fatemehsadat Mireshghallah, Zhijing Jin, Bernhard Schölkopf, Mrinmaya Sachan, Taylor Berg-Kirkpatrick
Membership Inference Attacks against Language Models via Neighbourhood Comparison. ACL (Findings) 2023: 11330-11343 - [c18]Fernando Gonzalez Adauto, Zhijing Jin, Bernhard Schölkopf, Tom Hope, Mrinmaya Sachan, Rada Mihalcea:
Beyond Good Intentions: Reporting the Research Landscape of NLP for Social Good. EMNLP (Findings) 2023: 415-438 - [c17]Zhijing Jin, Yuen Chen, Felix Leeb, Luigi Gresele, Ojasv Kamal, Zhiheng Lyu, Kevin Blin, Fernando Gonzalez Adauto, Max Kleiman-Weiner, Mrinmaya Sachan, Bernhard Schölkopf:
CLadder: A Benchmark to Assess Causal Reasoning Capabilities of Language Models. NeurIPS 2023 - [i37]Flavio Schneider, Zhijing Jin, Bernhard Schölkopf:
Moûsai: Text-to-Music Generation with Long-Context Latent Diffusion. CoRR abs/2301.11757 (2023) - [i36]Zhijing Jin, Rada Mihalcea:
Natural Language Processing for Policymaking. CoRR abs/2302.03490 (2023) - [i35]Zhiheng Lyu, Zhijing Jin, Justus Mattern, Rada Mihalcea, Mrinmaya Sachan, Bernhard Schölkopf:
Psychologically-Inspired Causal Prompts. CoRR abs/2305.01764 (2023) - [i34]Fernando Gonzalez, Zhijing Jin, Bernhard Schölkopf, Tom Hope, Mrinmaya Sachan, Rada Mihalcea:
Beyond Good Intentions: Reporting the Research Landscape of NLP for Social Good. CoRR abs/2305.05471 (2023) - [i33]Badr AlKhamissi, Siddharth Verma, Ping Yu, Zhijing Jin, Asli Celikyilmaz, Mona T. Diab:
OPT-R: Exploring the Role of Explanations in Finetuning and Prompting for Reasoning Skills of Large Language Models. CoRR abs/2305.12001 (2023) - [i32]Oana Ignat, Zhijing Jin, Artem Abzaliev, Laura Biester, Santiago Castro, Naihao Deng, Xinyi Gao, Aylin Gunal, Jacky He, Ashkan Kazemi, Muhammad Khalifa, Namho Koh, Andrew Lee, Siyang Liu, Do June Min, Shinka Mori, Joan Nwatu
A PhD Student's Perspective on Research in NLP in the Era of Very Large Language Models. CoRR abs/2305.12544 (2023) - [i31]Jingwei Ni, Zhijing Jin, Qian Wang, Mrinmaya Sachan, Markus Leippold:
When Does Aggregating Multiple Skills with Multi-Task Learning Work? A Case Study in Financial NLP. CoRR abs/2305.14007 (2023) - [i30]Yuxin Ren, Qipeng Guo, Zhijing Jin, Shauli Ravfogel, Mrinmaya Sachan, Bernhard Schölkopf, Ryan Cotterell:
All Roads Lead to Rome? Exploring the Invariance of Transformers' Representations. CoRR abs/2305.14555 (2023) - [i29]Yiwen Ding, Jiarui Liu, Zhiheng Lyu, Kun Zhang, Bernhard Schölkopf, Zhijing Jin, Rada Mihalcea:
Voices of Her: Analyzing Gender Differences in the AI Publication World. CoRR abs/2305.14597 (2023) - [i28]Justus Mattern, Fatemehsadat Mireshghallah, Zhijing Jin, Bernhard Schölkopf, Mrinmaya Sachan, Taylor Berg-Kirkpatrick:
Membership Inference Attacks against Language Models via Neighbourhood Comparison. CoRR abs/2305.18462 (2023) - [i27]Zhijing Jin, Jiarui Liu, Zhiheng Lyu, Spencer Poff, Mrinmaya Sachan, Rada Mihalcea, Mona T. Diab, Bernhard Schölkopf:
Can Large Language Models Infer Causation from Correlation? CoRR abs/2306.05836 (2023) - [i26]Ishan Kumar, Zhijing Jin, Ehsan Mokhtarian
CausalCite: A Causal Formulation of Paper Citations. CoRR abs/2311.02790 (2023) - [i25]David F. Jenny, Yann Billeter, Mrinmaya Sachan, Bernhard Schölkopf, Zhijing Jin:
Navigating the Ocean of Biases: Political Bias Attribution in Language Models via Causal Structures. CoRR abs/2311.08605 (2023) - [i24]Zhijing Jin, Yuen Chen, Felix Leeb, Luigi Gresele, Ojasv Kamal, Zhiheng Lyu, Kevin Blin, Fernando Gonzalez Adauto, Max Kleiman-Weiner, Mrinmaya Sachan, Bernhard Schölkopf:
CLadder: A Benchmark to Assess Causal Reasoning Capabilities of Language Models. CoRR abs/2312.04350 (2023) - 2022
- [j1]Di Jin, Zhijing Jin, Zhiting Hu, Olga Vechtomova, Rada Mihalcea:
Deep Learning for Text Style Transfer: A Survey. Comput. Linguistics 48(1): 155-205 (2022) - [c16]Daphna Keidar
Slangvolution: A Causal Analysis of Semantic Change and Frequency Dynamics in Slang. ACL (1) 2022: 1422-1442 - [c15]Sydney Levine, Zhijing Jin:
Competing perspectives on building ethical AI: psychological, philosophical, and computational approaches. CogSci 2022 - [c14]Justus Mattern, Zhijing Jin, Benjamin Weggenmann, Bernhard Schölkopf, Mrinmaya Sachan:
Differentially Private Language Models for Secure Data Sharing. EMNLP 2022: 4860-4873 - [c13]Zhijing Jin, Abhinav Lalwani, Tejas Vaidhya, Xiaoyu Shen, Yiwen Ding, Zhiheng Lyu, Mrinmaya Sachan, Rada Mihalcea, Bernhard Schölkopf:
Logical Fallacy Detection. EMNLP (Findings) 2022: 7180-7198 - [c12]Jingwei Ni, Zhijing Jin, Markus Freitag, Mrinmaya Sachan, Bernhard Schölkopf:
Original or Translated? A Causal Analysis of the Impact of Translationese on Machine Translation Performance. NAACL-HLT 2022: 5303-5320 - [c11]Zhijing Jin, Sydney Levine, Fernando Gonzalez Adauto, Ojasv Kamal, Maarten Sap, Mrinmaya Sachan, Rada Mihalcea, Josh Tenenbaum, Bernhard Schölkopf:
When to Make Exceptions: Exploring Language Models as Accounts of Human Moral Judgment. NeurIPS 2022 - [i23]Zhijing Jin, Abhinav Lalwani, Tejas Vaidhya, Xiaoyu Shen, Yiwen Ding, Zhiheng Lyu, Mrinmaya Sachan, Rada Mihalcea, Bernhard Schölkopf:
Logical Fallacy Detection. CoRR abs/2202.13758 (2022) - [i22]Daphna Keidar, Andreas Opedal, Zhijing Jin, Mrinmaya Sachan:
Slangvolution: A Causal Analysis of Semantic Change and Frequency Dynamics in Slang. CoRR abs/2203.04651 (2022) - [i21]Jingwei Ni, Zhijing Jin, Markus Freitag, Mrinmaya Sachan, Bernhard Schölkopf:
Original or Translated? A Causal Analysis of the Impact of Translationese on Machine Translation Performance. CoRR abs/2205.02293 (2022) - [i20]Zhijing Jin, Sydney Levine, Fernando Gonzalez, Ojasv Kamal, Maarten Sap, Mrinmaya Sachan, Rada Mihalcea, Josh Tenenbaum, Bernhard Schölkopf:
When to Make Exceptions: Exploring Language Models as Accounts of Human Moral Judgment. CoRR abs/2210.01478 (2022) - [i19]Dieuwke Hupkes, Mario Giulianelli, Verna Dankers, Mikel Artetxe, Yanai Elazar, Tiago Pimentel, Christos Christodoulopoulos, Karim Lasri, Naomi Saphra
State-of-the-art generalisation research in NLP: a taxonomy and review. CoRR abs/2210.03050 (2022) - [i18]Alessandro Stolfo, Zhijing Jin, Kumar Shridhar, Bernhard Schölkopf, Mrinmaya Sachan:
A Causal Framework to Quantify the Robustness of Mathematical Reasoning with Language Models. CoRR abs/2210.12023 (2022) - [i17]Justus Mattern, Zhijing Jin, Benjamin Weggenmann, Bernhard Schölkopf, Mrinmaya Sachan:
Differentially Private Language Models for Secure Data Sharing. CoRR abs/2210.13918 (2022) - [i16]Anna Costello, Ekaterina Fedorova, Zhijing Jin, Rada Mihalcea:
Editing a Woman's Voice. CoRR abs/2212.02581 (2022) - [i15]Justus Mattern, Zhijing Jin, Mrinmaya Sachan, Rada Mihalcea, Bernhard Schölkopf:
Understanding Stereotypes in Language Models: Towards Robust Measurement and Zero-Shot Debiasing. CoRR abs/2212.10678 (2022) - 2021
- [c10]Zhijing Jin, Geeticka Chauhan, Brian Tse, Mrinmaya Sachan, Rada Mihalcea:
How Good Is NLP? A Sober Look at NLP Tasks through the Lens of Social Impact. ACL/IJCNLP (Findings) 2021: 3099-3113 - [c9]Qipeng Guo, Zhijing Jin, Ziyu Wang, Xipeng Qiu, Weinan Zhang, Jun Zhu, Zheng Zhang, David Wipf:
Fork or Fail: Cycle-Consistent Training with Many-to-One Mappings. AISTATS 2021: 1828-1836 - [c8]Zhijing Jin, Zeyu Peng, Tejas Vaidhya, Bernhard Schölkopf, Rada Mihalcea:
Mining the Cause of Political Decision-Making from Social Media: A Case Study of COVID-19 Policies across the US States. EMNLP (Findings) 2021: 288-301 - [c7]Zhijing Jin, Julius von Kügelgen, Jingwei Ni, Tejas Vaidhya, Ayush Kaushal, Mrinmaya Sachan, Bernhard Schölkopf:
Causal Direction of Data Collection Matters: Implications of Causal and Anticausal Learning for NLP. EMNLP (1) 2021: 9499-9513 - [i14]Zhijing Jin, Geeticka Chauhan, Brian Tse, Mrinmaya Sachan, Rada Mihalcea:
How Good Is NLP? A Sober Look at NLP Tasks through the Lens of Social Impact. CoRR abs/2106.02359 (2021) - [i13]Zhijing Jin, Julius von Kügelgen, Jingwei Ni, Tejas Vaidhya, Ayush Kaushal, Mrinmaya Sachan, Bernhard Schölkopf:
Causal Direction of Data Collection Matters: Implications of Causal and Anticausal Learning for NLP. CoRR abs/2110.03618 (2021) - [i12]Hongru Wang, Zhijing Jin, Jiarun Cao, Gabriel Pui Cheong Fung, Kam-Fai Wong:
Inconsistent Few-Shot Relation Classification via Cross-Attentional Prototype Networks with Contrastive Learning. CoRR abs/2110.08254 (2021) - 2020
- [c6]Di Jin, Zhijing Jin, Joey Tianyi Zhou, Peter Szolovits:
Is BERT Really Robust? A Strong Baseline for Natural Language Attack on Text Classification and Entailment. AAAI 2020: 8018-8025 - [c5]Di Jin, Zhijing Jin, Joey Tianyi Zhou, Lisa Orii
Hooks in the Headline: Learning to Generate Headlines with Controlled Styles. ACL 2020: 5082-5093 - [c4]Zhijing Jin, Qipeng Guo, Xipeng Qiu, Zheng Zhang:
GenWiki: A Dataset of 1.3 Million Content-Sharing Text and Graphs for Unsupervised Graph-to-Text Generation. COLING 2020: 2398-2409 - [c3]Xiaoyu Xing, Zhijing Jin, Di Jin, Bingning Wang, Qi Zhang, Xuanjing Huang:
Tasty Burgers, Soggy Fries: Probing Aspect Robustness in Aspect-Based Sentiment Analysis. EMNLP (1) 2020: 3594-3605 - [i11]Di Jin, Zhijing Jin, Joey Tianyi Zhou, Peter Szolovits:
Unsupervised Domain Adaptation for Neural Machine Translation with Iterative Back Translation. CoRR abs/2001.08140 (2020) - [i10]Di Jin, Zhijing Jin, Joey Tianyi Zhou, Lisa Orii, Peter Szolovits:
Hooks in the Headline: Learning to Generate Headlines with Controlled Styles. CoRR abs/2004.01980 (2020) - [i9]Zhijing Jin, Yongyi Yang, Xipeng Qiu, Zheng Zhang:
Relation of the Relations: A New Paradigm of the Relation Extraction Problem. CoRR abs/2006.03719 (2020) - [i8]Qipeng Guo, Zhijing Jin, Xipeng Qiu, Weinan Zhang, David Wipf, Zheng Zhang:
CycleGT: Unsupervised Graph-to-Text and Text-to-Graph Generation via Cycle Training. CoRR abs/2006.04702 (2020) - [i7]Xiaoyu Xing, Zhijing Jin, Di Jin, Bingning Wang, Qi Zhang, Xuanjing Huang:
Tasty Burgers, Soggy Fries: Probing Aspect Robustness in Aspect-Based Sentiment Analysis. CoRR abs/2009.07964 (2020) - [i6]Di Jin, Zhijing Jin, Zhiting Hu, Olga Vechtomova, Rada Mihalcea:
Deep Learning for Text Style Transfer: A Survey. CoRR abs/2011.00416 (2020) - [i5]Qipeng Guo, Zhijing Jin, Ziyu Wang, Xipeng Qiu, Weinan Zhang, Jun Zhu, Zheng Zhang, David Wipf:
Fork or Fail: Cycle-Consistent Training with Many-to-One Mappings. CoRR abs/2012.07412 (2020)
2010 – 2019
- 2019
- [c2]Zhijing Jin, Di Jin, Jonas Mueller, Nicholas Matthews, Enrico Santus:
IMaT: Unsupervised Text Attribute Transfer via Iterative Matching and Translation. EMNLP/IJCNLP (1) 2019: 3095-3107 - [c1]Yujie Qian, Enrico Santus, Zhijing Jin, Jiang Guo, Regina Barzilay:
GraphIE: A Graph-Based Framework for Information Extraction. NAACL-HLT (1) 2019: 751-761 - [i4]Zhijing Jin, Di Jin, Jonas Mueller, Nicholas Matthews, Enrico Santus:
Unsupervised Text Style Transfer via Iterative Matching and Translation. CoRR abs/1901.11333 (2019) - [i3]Di Jin, Zhijing Jin, Joey Tianyi Zhou, Peter Szolovits:
Is BERT Really Robust? Natural Language Attack on Text Classification and Entailment. CoRR abs/1907.11932 (2019) - 2018
- [i2]Zhijing Jin, Tristan Swedish, Ramesh Raskar:
3D Traffic Simulation for Autonomous Vehicles in Unity and Python. CoRR abs/1810.12552 (2018) - [i1]Yujie Qian, Enrico Santus, Zhijing Jin, Jiang Guo, Regina Barzilay:
GraphIE: A Graph-Based Framework for Information Extraction. CoRR abs/1810.13083 (2018)
Coauthor Index
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