Ning Ding
Tsinghua researcher known for parameter-efficient fine-tuning, UltraFeedback, and OpenBMB open-source LLM tooling.
- Role
- researcher
- Currently at
- Tsinghua University
- GitHub
- github.com/ningding97
- Scholar
- scholar.google.com/citations
- Papers
- 45
Cite
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Authored papers
45Rethinking On-Policy Distillation of Large Language Models: Phenomenology, Mechanism, and Recipe
arXiv 2026
Post-Trained MoE Can Skip Half Experts via Self-Distillation
arXiv 2026
AI Can Learn Scientific Taste
arXiv 2026
Toward Efficient Agents: Memory, Tool learning, and Planning
arXiv 2026
MeKi: Memory-based Expert Knowledge Injection for Efficient LLM Scaling
arXiv 2026
P1-VL: Bridging Visual Perception and Scientific Reasoning in Physics Olympiads
arXiv 2026
SimpleVLA-RL: Scaling VLA Training via Reinforcement Learning
arXiv 2025
TTRL: Test-Time Reinforcement Learning
arXiv 2025
MiniCPM4: Ultra-Efficient LLMs on End Devices
arXiv 2025
The Entropy Mechanism of Reinforcement Learning for Reasoning Language Models
arXiv 2025
Process Reinforcement through Implicit Rewards
arXiv 2025
MedXpertQA: Benchmarking Expert-Level Medical Reasoning and Understanding
arXiv 2025
Farseer: A Refined Scaling Law in Large Language Models
arXiv 2025
MiniCPM-V 4.5: Cooking Efficient MLLMs via Architecture, Data, and Training Recipe
arXiv 2025
FlowRL: Matching Reward Distributions for LLM Reasoning
arXiv 2025
A Survey of Reinforcement Learning for Large Reasoning Models
arXiv 2025
P1: Mastering Physics Olympiads with Reinforcement Learning
arXiv 2025
UltraIF: Advancing Instruction Following from the Wild
arXiv 2025
EAQuant: Enhancing Post-Training Quantization for MoE Models via Expert-Aware Optimization
arXiv 2025
SSRL: Self-Search Reinforcement Learning
arXiv 2025
Towards a Unified View of Large Language Model Post-Training
arXiv 2025
From f(x) and g(x) to f(g(x)): LLMs Learn New Skills in RL by Composing Old Ones
arXiv 2025
RLPR: Extrapolating RLVR to General Domains without Verifiers
arXiv 2025
From AI for Science to Agentic Science: A Survey on Autonomous Scientific Discovery
arXiv 2025
JustRL: Scaling a 1.5B LLM with a Simple RL Recipe
arXiv 2025
UltraLink: An Open-Source Knowledge-Enhanced Multilingual Supervised Fine-tuning Dataset
arXiv 2024
Intuitive Fine-Tuning: Towards Simplifying Alignment into a Single Process
arXiv 2024
Controllable Preference Optimization: Toward Controllable Multi-Objective Alignment
arXiv 2024
Fast and Slow Generating: An Empirical Study on Large and Small Language Models Collaborative Decoding
arXiv 2024
How to Synthesize Text Data without Model Collapse?
arXiv 2024
Advancing LLM Reasoning Generalists with Preference Trees
arXiv 2024
UltraMedical: Building Specialized Generalists in Biomedicine
arXiv 2024
Free Process Rewards without Process Labels
arXiv 2024
Fourier Position Embedding: Enhancing Attention's Periodic Extension for Length Generalization
arXiv 2024
Enhancing Chat Language Models by Scaling High-quality Instructional Conversations
EMNLP
UltraFeedback: Boosting Language Models with High-quality Feedback
ICML
GPT4Image: Can Large Pre-trained Models Help Vision Models on Perception Tasks?
arXiv 2023
KoLA: Carefully Benchmarking World Knowledge of Large Language Models
arXiv 2023
CRaSh: Clustering, Removing, and Sharing Enhance Fine-tuning without Full Large Language Model
arXiv 2023
Exploring the Impact of Model Scaling on Parameter-Efficient Tuning
arXiv 2023
Tool Learning with Foundation Models
arXiv 2023
OpenDelta: A Plug-and-play Library for Parameter-efficient Adaptation of Pre-trained Models
arXiv 2023
Sparse Low-rank Adaptation of Pre-trained Language Models
arXiv 2023
OpenPrompt: An Open-source Framework for Prompt-learning
ACL 2022 5
Few-NERD: A Few-Shot Named Entity Recognition Dataset
ACL 2021 5
Tool contributions
1Affiliations
Previously
Frequent co-authors
10from 45 papers
Bowen Zhou
professor
Zhiyuan Liu
professor
Ganqu Cui
researcher
Kaiyan Zhang
Maosong Sun
professor
Yuxin Zuo
Xingtai Lv
Xuekai Zhu
Ermo Hua
Lifan Yuan
grad-student