Haoming Jiang
43 papers · 2019–2025 · 9 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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πΊοΈ Taxonomy Completionist (89) π Academic Marathon Β· Sprint π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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(30)
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Topic Evolution
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Keyword Pioneer
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Triple Crown
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Mega-Team Β· Squad
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Conference Pioneer
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Unstoppable Β· Bronze
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The Questioner
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Prolific Year Β· Productive
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Century Club Β· Bronze
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Renaissance Researcher
(7)
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Trend Setter
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Keyword Collector
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Research topics
Machine Learning
(32)
Natural Language Processing
(20)
Deep Learning
(19)
Artificial Intelligence
(18)
Optimization & Theory Β· Machine Learning
(17)
Core AI
(16)
Learning Types Β· Machine Learning
(15)
Applications
(9)
Architectures
(9)
Resources & Methods
(9)
Application Areas
(8)
Learning Types Β· Deep Learning
(8)
Generation
(6)
Optimization & Theory Β· Deep Learning
(5)
Mathematics & Optimization
(4)
Keywords
deep learning
(3)
neural machine translation
(3)
question answering
(3)
language model
(3)
pre-trained language model
(3)
domain adaptation
(3)
event sequence
(3)
adaptive learning rate
(2)
neural network optimization
(2)
reward learning
(2)
weak supervision
(2)
instruction following
(2)
reinforcement learning from human feedback
(2)
point process
(2)
adversarial training
(2)
language model alignment
(2)
model compression
(2)
few-shot learning
(2)
text generation
(2)
transfer learning
(2)
Papers
Can Language Models Follow Multiple Turns of Entangled Instructions?
EMNLP 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
Hephaestus: Improving Fundamental Agent Capabilities of Large Language Models through Continual Pre-Training
NAACL 2025
IHEval: Evaluating Language Models on Following the Instruction Hierarchy
NAACL 2025
Improving Large Language Models Function Calling and Interpretability via Guided-Structured Templates
EMNLP 2025
Adaptive Preference Scaling for Reinforcement Learning with Human Feedback
NeurIPS 2024
BlendFilter: Advancing Retrieval-Augmented Large Language Models via Query Generation Blending and Knowledge Filtering
EMNLP 2024
Data Diversity Matters for Robust Instruction Tuning
EMNLP 2024
Large Language Models Are Poor Clinical Decision-Makers: A Comprehensive Benchmark
EMNLP 2024
MEMORYLLM: Towards Self-Updatable Large Language Models
ICML 2024
Robust Reinforcement Learning from Corrupted Human Feedback
NeurIPS 2024
Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation
NeurIPS 2023
Context-Aware Query Rewriting for Improving Usersβ 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
Knowledge-Selective Pretraining for Attribute Value Extraction
EMNLP 2023
SMURF-THP: Score Matching-based UnceRtainty quantiFication for Transformer Hawkes Process
ICML 2023
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
Self-Training with Differentiable Teacher
NAACL 2022
SEQZERO: Few-shot Compositional Semantic Parsing with Sequential Prompts and Zero-shot Models
NAACL 2022
Adversarial Regularization as Stackelberg Game: An Unrolled Optimization Approach
EMNLP 2021
ARCH: Efficient Adversarial Regularized Training with Caching
EMNLP 2021
Fine-Tuning Pre-trained Language Model with Weak Supervision: A Contrastive-Regularized Self-Training Approach
NAACL 2021
Learning to Defend by Learning to Attack
AISTATS 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
Token-wise Curriculum Learning for Neural Machine Translation
EMNLP 2021
Towards Automatic Evaluation of Dialog Systems: A Model-Free Off-Policy Evaluation Approach
EMNLP 2021
Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data
EMNLP 2020
Deep Reinforcement Learning with Robust and Smooth Policy
ICML 2020
Multi-Domain Neural Machine Translation with Word-Level Adaptive Layer-wise Domain Mixing
ACL 2020
On the Variance of the Adaptive Learning Rate and Beyond
ICLR 2020
SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization
ACL 2020
Transformer Hawkes Process
ICML 2020
Contextual Text Denoising with Masked Language Model
EMNLP 2019
Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds
NeurIPS 2019
Meta Learning with Relational Information for Short Sequences
NeurIPS 2019
On Computation and Generalization of Generative Adversarial Networks under Spectrum Control
ICLR 2019
On Fast Convergence of Proximal Algorithms for SQRT-Lasso Optimization: Donβt Worry About its Nonsmooth Loss Function
UAI 2019
On Scalable and Efficient Computation of Large Scale Optimal Transport
ICML 2019
Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python
JMLR 2019