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Haoming Jiang

45 papers · 2019–2025 · 10 conferences · across top CS/AI conferences

Achievements

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+15 more ↓ πŸ—ΊοΈ Taxonomy Completionist (14) 🧭 Keyword Pioneer πŸŒ‰ Interdisciplinary Bridge 🌈 Renaissance Researcher (6) 🌍 Conference Polyglot (10)
🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (14) 🀝 Dynamic Duo (32) πŸ‘‘ Triple Crown πŸ‘₯ Mega-Team (20) 🌱 Topic Pioneer πŸ”¬ Deep Specialist (10) 🧬 Topic Evolution ⚑ Prolific Year (6) ❓ The Questioner πŸ’Ž Century Club (45) πŸš€ Conference Pioneer πŸ”₯ Unstoppable (7) πŸ—ƒοΈ Keyword Collector (189)

Conferences

EMNLP (13) ACL (7) ICML (6) NAACL (5) NIPS (5) ICLR (4) IJCNLP (2) AISTATS (1) JMLR (1) UAI (1)

Top co-authors

Tuo Zhao (32) Bing Yin (17) Simiao Zuo (10) Zheng Li (10) Chao Zhang (10) Chen Liang (9) Weizhu Chen (8) Xiaodong Liu (8) Pengcheng He (8) Qingyu Yin (8)

Keywords

question answering (3) language model (3) event sequence (3) named entity recognition (3) deep learning (3) neural machine translation (3) weak supervision (3) pre-trained language model (3) domain adaptation (3) point process (2) lottery ticket hypothesis (2) neural network optimization (2) few-shot learning (2) reinforcement learning from human feedback (2) reward learning (2) language model alignment (2) instruction following (2) natural language understanding (2) transfer learning (2) text generation (2)

Papers

Hephaestus: Improving Fundamental Agent Capabilities of Large Language Models through Continual Pre-Training NAACL 2025 Discriminative Finetuning of Generative Large Language Models without Reward Models and Human Preference Data ICML 2025 DORM: Preference Data Weights Optimization for Reward Modeling in LLM Alignment EMNLP 2025 Can Language Models Follow Multiple Turns of Entangled Instructions? EMNLP 2025 Improving Large Language Models Function Calling and Interpretability via Guided-Structured Templates EMNLP 2025 IHEval: Evaluating Language Models on Following the Instruction Hierarchy NAACL 2025 Data Diversity Matters for Robust Instruction Tuning EMNLP 2024 MEMORYLLM: Towards Self-Updatable Large Language Models ICML 2024 Adaptive Preference Scaling for Reinforcement Learning with Human Feedback NIPS 2024 Robust Reinforcement Learning from Corrupted Human Feedback NIPS 2024 BlendFilter: Advancing Retrieval-Augmented Large Language Models via Query Generation Blending and Knowledge Filtering EMNLP 2024 Large Language Models Are Poor Clinical Decision-Makers: A Comprehensive Benchmark EMNLP 2024 SMURF-THP: Score Matching-based UnceRtainty quantiFication for Transformer Hawkes Process ICML 2023 Knowledge-Selective Pretraining for Attribute Value Extraction EMNLP 2023 Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation NIPS 2023 Context-Aware Query Rewriting for Improving Users’ Search Experience on E-commerce Websites ACL 2023 Graph Reasoning for Question Answering with Triplet Retrieval ACL 2023 HomoDistil: Homotopic Task-Agnostic Distillation of Pre-trained Transformers ICLR 2023 SEQZERO: Few-shot Compositional Semantic Parsing with Sequential Prompts and Zero-shot Models NAACL 2022 Self-Training with Differentiable Teacher NAACL 2022 Multilingual Knowledge Graph Completion with Self-Supervised Adaptive Graph Alignment ACL 2022 No Parameters Left Behind: Sensitivity Guided Adaptive Learning Rate for Training Large Transformer Models ICLR 2022 Fine-Tuning Pre-trained Language Model with Weak Supervision: A Contrastive-Regularized Self-Training Approach NAACL 2021 Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data ACL 2021 Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization ACL 2021 Learning to Defend by Learning to Attack AISTATS 2021 Adversarial Regularization as Stackelberg Game: An Unrolled Optimization Approach EMNLP 2021 Towards Automatic Evaluation of Dialog Systems: A Model-Free Off-Policy Evaluation Approach EMNLP 2021 Token-wise Curriculum Learning for Neural Machine Translation EMNLP 2021 ARCH: Efficient Adversarial Regularized Training with Caching EMNLP 2021 Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data IJCNLP 2021 Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization IJCNLP 2021 Transformer Hawkes Process ICML 2020 On the Variance of the Adaptive Learning Rate and Beyond ICLR 2020 Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data EMNLP 2020 SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization ACL 2020 Multi-Domain Neural Machine Translation with Word-Level Adaptive Layer-wise Domain Mixing ACL 2020 Deep Reinforcement Learning with Robust and Smooth Policy ICML 2020 Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python JMLR 2019 Meta Learning with Relational Information for Short Sequences NIPS 2019 Contextual Text Denoising with Masked Language Model EMNLP 2019 On Computation and Generalization of Generative Adversarial Networks under Spectrum Control ICLR 2019 On Scalable and Efficient Computation of Large Scale Optimal Transport ICML 2019 Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds NIPS 2019 On Fast Convergence of Proximal Algorithms for SQRT-Lasso Optimization: Don’t Worry About its Nonsmooth Loss Function UAI 2019