← Authors

Haoming Jiang

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

Achievements

🧭 Keyword Pioneer 🌍 Conference Polyglot (10) 🐝 Cross-Pollinator (5) 🐣 Hot Topic Early Bird πŸƒ Academic Marathon (6) 🌈 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