Haoming Jiang

Orcid: 0000-0003-0789-525X

According to our database1, Haoming Jiang authored at least 62 papers between 2018 and 2024.

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

Timeline

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Bibliography

2024
Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond.
ACM Trans. Knowl. Discov. Data, July, 2024

RNR: Teaching Large Language Models to Follow Roles and Rules.
CoRR, 2024

Inductive or Deductive? Rethinking the Fundamental Reasoning Abilities of LLMs.
CoRR, 2024

Relational Database Augmented Large Language Model.
CoRR, 2024

Robust Reinforcement Learning from Corrupted Human Feedback.
CoRR, 2024

Adaptive Preference Scaling for Reinforcement Learning with Human Feedback.
CoRR, 2024

MEMORYLLM: Towards Self-Updatable Large Language Models.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

BlendFilter: Advancing Retrieval-Augmented Large Language Models via Query Generation Blending and Knowledge Filtering.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Large Language Models Are Poor Clinical Decision-Makers: A Comprehensive Benchmark.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Data Diversity Matters for Robust Instruction Tuning.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

2023
Situated Natural Language Explanations.
CoRR, 2023

CCGen: Explainable Complementary Concept Generation in E-Commerce.
CoRR, 2023

Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond.
CoRR, 2023

HomoDistil: Homotopic Task-Agnostic Distillation of Pre-trained Transformers.
CoRR, 2023

Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

LightToken: A Task and Model-agnostic Lightweight Token Embedding Framework for Pre-trained Language Models.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

SMURF-THP: Score Matching-based UnceRtainty quantiFication for Transformer Hawkes Process.
Proceedings of the International Conference on Machine Learning, 2023

HomoDistil: Homotopic Task-Agnostic Distillation of Pre-trained Transformers.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Knowledge-Selective Pretraining for Attribute Value Extraction.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

SST: Semantic and Structural Transformers for Hierarchy-aware Language Models in E-commerce.
Proceedings of the IEEE International Conference on Big Data, 2023

Context-Aware Query Rewriting for Improving Users' Search Experience on E-commerce Websites.
Proceedings of the The 61st Annual Meeting of the Association for Computational Linguistics: Industry Track, 2023

Graph Reasoning for Question Answering with Triplet Retrieval.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022
Short Text Pre-training with Extended Token Classification for E-commerce Query Understanding.
CoRR, 2022

DiP-GNN: Discriminative Pre-Training of Graph Neural Networks.
CoRR, 2022

Condensing Graphs via One-Step Gradient Matching.
CoRR, 2022

Query Attribute Recommendation at Amazon Search.
Proceedings of the RecSys '22: Sixteenth ACM Conference on Recommender Systems, Seattle, WA, USA, September 18, 2022

Self-Training with Differentiable Teacher.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2022, 2022

SEQZERO: Few-shot Compositional Semantic Parsing with Sequential Prompts and Zero-shot Models.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2022, 2022

AutoGDA: Automated Graph Data Augmentation for Node Classification.
Proceedings of the Learning on Graphs Conference, 2022

Condensing Graphs via One-Step Gradient Matching.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

No Parameters Left Behind: Sensitivity Guided Adaptive Learning Rate for Training Large Transformer Models.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Multilingual Knowledge Graph Completion with Self-Supervised Adaptive Graph Alignment.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021
Reducing Human Labor Cost in Deep Learning for Natural Language Processing.
PhD thesis, 2021

Adversarial Training as Stackelberg Game: An Unrolled Optimization Approach.
CoRR, 2021

Fine-Tuning Pre-trained Language Model with Weak Supervision: A Contrastive-Regularized Self-Training Approach.
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Adversarial Regularization as Stackelberg Game: An Unrolled Optimization Approach.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

ARCH: Efficient Adversarial Regularized Training with Caching.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

Token-wise Curriculum Learning for Neural Machine Translation.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

Towards Automatic Evaluation of Dialog Systems: A Model-Free Off-Policy Evaluation Approach.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Learning to Defend by Learning to Attack.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020
Deep Reinforcement Learning with Smooth Policy.
CoRR, 2020

BOND: BERT-Assisted Open-Domain Named Entity Recognition with Distant Supervision.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Transformer Hawkes Process.
Proceedings of the 37th International Conference on Machine Learning, 2020

Deep Reinforcement Learning with Robust and Smooth Policy.
Proceedings of the 37th International Conference on Machine Learning, 2020

On the Variance of the Adaptive Learning Rate and Beyond.
Proceedings of the 8th International Conference on Learning Representations, 2020

Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Multi-Domain Neural Machine Translation with Word-Level Adaptive Layer-wise Domain Mixing.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019
Designing deployable 3D scissor structures with ball-and-socket joints.
Comput. Animat. Virtual Worlds, 2019

Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python.
J. Mach. Learn. Res., 2019

Contextual Text Denoising with Masked Language Models.
CoRR, 2019

On Fast Convergence of Proximal Algorithms for SQRT-Lasso Optimization: Don't Worry About its Nonsmooth Loss Function.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Meta Learning with Relational Information for Short Sequences.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

On Scalable and Efficient Computation of Large Scale Optimal Transport.
Proceedings of the 36th International Conference on Machine Learning, 2019

On Computation and Generalization of Generative Adversarial Networks under Spectrum Control.
Proceedings of the 7th International Conference on Learning Representations, 2019

Learning to Defense by Learning to Attack.
Proceedings of the Deep Generative Models for Highly Structured Data, 2019

Contextual Text Denoising with Masked Language Model.
Proceedings of the 5th Workshop on Noisy User-generated Text, 2019

2018
On Computation and Generalization of GANs with Spectrum Control.
CoRR, 2018

Learning to Defense by Learning to Attack.
CoRR, 2018


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