Wanjun Zhong

Orcid: 0009-0007-2236-228X

According to our database1, Wanjun Zhong authored at least 51 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
CLUE: Contrastive language-guided learning for referring video object segmentation.
Pattern Recognit. Lett., 2024

AutoKaggle: A Multi-Agent Framework for Autonomous Data Science Competitions.
CoRR, 2024

Agents in Software Engineering: Survey, Landscape, and Vision.
CoRR, 2024

CLongEval: A Chinese Benchmark for Evaluating Long-Context Large Language Models.
CoRR, 2024

PerLTQA: A Personal Long-Term Memory Dataset for Memory Classification, Retrieval, and Synthesis in Question Answering.
CoRR, 2024

YODA: Teacher-Student Progressive Learning for Language Models.
CoRR, 2024

AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2024, 2024

When to Stop? Towards Efficient Code Generation in LLMs with Excess Token Prevention.
Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis, 2024

CLongEval: A Chinese Benchmark for Evaluating Long-Context Large Language Models.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

Concise and Precise Context Compression for Tool-Using Language Models.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

Learning to Edit: Aligning LLMs with Knowledge Editing.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

FollowBench: A Multi-level Fine-grained Constraints Following Benchmark for Large Language Models.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

Planning, Creation, Usage: Benchmarking LLMs for Comprehensive Tool Utilization in Real-World Complex Scenarios.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

Abstract Meaning Representation-Based Logic-Driven Data Augmentation for Logical Reasoning.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

MemoryBank: Enhancing Large Language Models with Long-Term Memory.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Improving task generalization via unified schema prompt.
AI Open, January, 2023

G-LLaVA: Solving Geometric Problem with Multi-Modal Large Language Model.
CoRR, 2023

Data Management For Large Language Models: A Survey.
CoRR, 2023

A Systematic Evaluation of Large Language Models on Out-of-Distribution Logical Reasoning Tasks.
CoRR, 2023

Adaptive-Solver Framework for Dynamic Strategy Selection in Large Language Model Reasoning.
CoRR, 2023

SELF: Language-Driven Self-Evolution for Large Language Model.
CoRR, 2023

Exploring Self-Reinforcement for Improving Learnersourced Multiple-Choice Question Explanations with Large Language Models.
CoRR, 2023

Aligning Large Language Models with Human: A Survey.
CoRR, 2023

GroundNLQ @ Ego4D Natural Language Queries Challenge 2023.
CoRR, 2023

Contrastive Learning with Logic-driven Data Augmentation for Logical Reasoning over Text.
CoRR, 2023

You Augment Me: Exploring ChatGPT-based Data Augmentation for Semantic Code Search.
Proceedings of the IEEE International Conference on Software Maintenance and Evolution, 2023

Cross-Modal-Aware Representation Learning with Syntactic Hypergraph Convolutional Network for VideoQA.
Proceedings of the IEEE International Conference on Multimedia and Expo, 2023

Leveraging Visual Prompts To Guide Language Modeling for Referring Video Object Segmentation.
Proceedings of the IEEE International Conference on Image Processing, 2023

Disentangling Reasoning Capabilities from Language Models with Compositional Reasoning Transformers.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

CONE: An Efficient COarse-to-fiNE Alignment Framework for Long Video Temporal Grounding.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022
From LSAT: The Progress and Challenges of Complex Reasoning.
IEEE ACM Trans. Audio Speech Lang. Process., 2022

An Efficient COarse-to-fiNE Alignment Framework @ Ego4D Natural Language Queries Challenge 2022.
CoRR, 2022

Modeling Semantic Composition with Syntactic Hypergraph for Video Question Answering.
CoRR, 2022

Reasoning over Hybrid Chain for Table-and-Text Open Domain QA.
CoRR, 2022

LogiGAN: Learning Logical Reasoning via Adversarial Pre-training.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Analytical Reasoning of Text.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2022, 2022

ProQA: Structural Prompt-based Pre-training for Unified Question Answering.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Reasoning over Hybrid Chain for Table-and-Text Open Domain Question Answering.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Mixed-modality Representation Learning and Pre-training for Joint Table-and-Text Retrieval in OpenQA.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Logic-Driven Context Extension and Data Augmentation for Logical Reasoning of Text.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

2021
AR-LSAT: Investigating Analytical Reasoning of Text.
CoRR, 2021

WhiteningBERT: An Easy Unsupervised Sentence Embedding Approach.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

UserAdapter: Few-Shot User Learning in Sentiment Analysis.
Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

Syntax-Enhanced Pre-trained Model.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

Compare to The Knowledge: Graph Neural Fake News Detection with External Knowledge.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020
A Heterogeneous Graph with Factual, Temporal and Logical Knowledge for Question Answering Over Dynamic Contexts.
CoRR, 2020

Neural Deepfake Detection with Factual Structure of Text.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Leveraging Declarative Knowledge in Text and First-Order Logic for Fine-Grained Propaganda Detection.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Reasoning Over Semantic-Level Graph for Fact Checking.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

LogicalFactChecker: Leveraging Logical Operations for Fact Checking with Graph Module Network.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019
Improving Question Answering by Commonsense-Based Pre-training.
Proceedings of the Natural Language Processing and Chinese Computing, 2019


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