← Authors

Tianlong Chen

158 papers · 2019–2026 · 16 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🌈 Renaissance Researcher (11) 🐝 Cross-Pollinator (7) πŸƒ Academic Marathon (6) 🌍 Conference Polyglot (16) πŸŒ‰ Interdisciplinary Bridge 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (20) 🌟 Keyword Trendsetter Combo (3) 🏠 Conference Loyalist (25) πŸ‘₯ Mega-Team (71) πŸ‘‘ Triple Crown πŸ† Grand Slam πŸ”¬ Deep Specialist (20) 🧬 Topic Evolution πŸ† Keyword Champion (17) 🀝 Dynamic Duo (87) πŸ—ƒοΈ Keyword Collector (61) πŸ’Ž Century Club (153) πŸš€ Conference Pioneer ⚑ Prolific Year (18) πŸ”₯ Unstoppable (7) ❓ The Questioner (4) πŸ“ˆ Trend Setter

Conferences

ICLR (32) ICML (26) NIPS (25) AAAI (14) EMNLP (14) ACL (12) CVPR (10) ECCV (6) ICCV (5) NAACL (5) WACV (3) EACL (2) AISTATS (1) AUTOML (1) INTERSPEECH (1) JMLR (1)

Top co-authors

Zhangyang Wang (87) Xuxi Chen (19) Zhenyu Zhang (18) Zhen Tan (16) Yu Cheng (16) Sijia Liu (15) Jie Peng (14) Shiwei Liu (14) Shiyu Chang (12) Pingzhi Li (11)

Research topics

Reinforcement Learning (1) Probability (1)

Keywords

large language model (22) lottery ticket hypothesis (17) model compression (17) network pruning (14) graph neural network (11) representation learning (10) self-supervised learning (9) adversarial training (9) neural network pruning (9) transfer learning (8) mixture of expert (8) contrastive learning (7) sparse training (6) neural network optimization (6) vision transformer (6) adversarial robustness (6) reinforcement learning (5) learning to optimize (5) iterative magnitude pruning (5) neural network (5)

Papers

Dialogue is Better Than Monologue: Instructing Meidcal LLMs via Strategic Conversations EACL 2026
OR-R1: Automating Modeling and Solving of Operations Research Optimization Problem via Test-Time Reinforcement Learning AAAI 2026
Vulnerability-Aware Robust Multimodal Adversarial Training AAAI 2026
Model Editing as a Double-Edged Sword: Steering Agent Behavior Toward Beneficence or Harm AAAI 2026
COIN: Uncertainty-Guarding Selective Question Answering for Foundation Models with Provable Risk Guarantees AAAI 2026
Layer-Level Self-Exposure and Patch: Affirmative Token Mitigation for Jailbreak Attack Defense NAACL 2025
BPO: Towards Balanced Preference Optimization between Knowledge Breadth and Depth in Alignment NAACL 2025
Advancing MoE Efficiency: A Collaboration-Constrained Routing (C2R) Strategy for Better Expert Parallelism Design NAACL 2025
GuideLLM: Exploring LLM-Guided Conversation with Applications in Autobiography Interviewing NAACL 2025
G-Designer: Architecting Multi-agent Communication Topologies via Graph Neural Networks ICML 2025
$\textttI$^2$MoE$: Interpretable Multimodal Interaction-aware Mixture-of-Experts ICML 2025
Modalities Contribute Unequally: Enhancing Medical Multi-modal Learning through Adaptive Modality Token Re-balancing ICML 2025
Occult: Optimizing Collaborative Communications across Experts for Accelerated Parallel MoE Training and Inference ICML 2025
EQA-RM: A Generative Embodied Reward Model with Test-time Scaling EMNLP 2025
MedHallu: A Comprehensive Benchmark for Detecting Medical Hallucinations in Large Language Models EMNLP 2025
Glider: Global and Local Instruction-Driven Expert Router EMNLP 2025
Bit-Flip Error Resilience in LLMs: A Comprehensive Analysis and Defense Framework EMNLP 2025
AnyMAC: Cascading Flexible Multi-Agent Collaboration via Next-Agent Prediction EMNLP 2025
BrainMAP: Learning Multiple Activation Pathways in Brain Networks AAAI 2025
DLF: Disentangled-Language-Focused Multimodal Sentiment Analysis AAAI 2025
Mapping from Meaning: Addressing the Miscalibration of Prompt-Sensitive Language Models AAAI 2025
Tuning-Free Accountable Intervention for LLM Deployment – a Metacognitive Approach AAAI 2025
Breaking the Resource Monopoly from Industries: Sustainable and Reliable LLM Serving by Recycling Outdated and Resource-Constrained GPUs AAAI 2025
In Prospect and Retrospect: Reflective Memory Management for Long-term Personalized Dialogue Agents ACL 2025
SCALE: Towards Collaborative Content Analysis in Social Science with Large Language Model Agents and Human Intervention ACL 2025
Agents Under Siege: Breaking Pragmatic Multi-Agent LLM Systems with Optimized Prompt Attacks ACL 2025
SConU: Selective Conformal Uncertainty in Large Language Models ACL 2025
The Efficiency vs. Accuracy Trade-off: Optimizing RAG-Enhanced LLM Recommender Systems Using Multi-Head Early Exit ACL 2025
UQ-Merge: Uncertainty Guided Multimodal Large Language Model Merging ACL 2025
GRNFormer: A Biologically-Guided Framework for Integrating Gene Regulatory Networks into RNA Foundation Models ACL 2025
Vision Language Model Helps Private Information De-Identification in Vision Data ACL 2025
Unveiling Privacy Risks in Multi-modal Large Language Models: Task-specific Vulnerabilities and Mitigation Challenges ACL 2025
Spatial Coordinates as a Cell Language: A Multi-Sentence Framework for Imaging Mass Cytometry Analysis ACL 2025
Proactive Privacy Amnesia for Large Language Models: Safeguarding PII with Negligible Impact on Model Utility ICLR 2025
Adapt-$\infty$: Scalable Continual Multimodal Instruction Tuning via Dynamic Data Selection ICLR 2025
Graph Sparsification via Mixture of Graphs ICLR 2025
Composable Interventions for Language Models ICLR 2025
PortLLM: Personalizing Evolving Large Language Models with Training-Free and Portable Model Patches ICLR 2025
Towards Stabilized and Efficient Diffusion Transformers through Long-Skip-Connections with Spectral Constraints ICCV 2025
FIER: Fine-Grained and Efficient KV Cache Retrieval for Long-context LLM Inference EMNLP 2025
ORAL: Prompting Your Large-Scale LoRAs via Conditional Recurrent Diffusion EMNLP 2025
Bag of Tricks for Sparse Mixture-of-Experts: A Benchmark Across Reasoning, Efficiency, and Safety EMNLP 2025
Task-Aware Resolution Optimization for Visual Large Language Models EMNLP 2025
Cut the Crap: An Economical Communication Pipeline for LLM-based Multi-Agent Systems ICLR 2025
Visual Prompting Upgrades Neural Network Sparsification: A Data-Model Perspective AAAI 2025
Sparse Transfer Learning Accelerates and Enhances Certified Robustness: A Comprehensive Study AAAI 2025
Position: TrustLLM: Trustworthiness in Large Language Models ICML 2024
Evolution-Inspired Loss Functions for Protein Representation Learning ICML 2024
Sparse Cocktail: Every Sparse Pattern Every Sparse Ratio All At Once ICML 2024
$\texttt{Model-GLUE}$: Democratized LLM Scaling for A Large Model Zoo in the Wild NIPS 2024
GTBench: Uncovering the Strategic Reasoning Capabilities of LLMs via Game-Theoretic Evaluations NIPS 2024
GDeR: Safeguarding Efficiency, Balancing, and Robustness via Prototypical Graph Pruning NIPS 2024
Flex-MoE: Modeling Arbitrary Modality Combination via the Flexible Mixture-of-Experts NIPS 2024
$\textttMoE-RBench$: Towards Building Reliable Language Models with Sparse Mixture-of-Experts ICML 2024
Glue pizza and eat rocks - Exploiting Vulnerabilities in Retrieval-Augmented Generative Models EMNLP 2024
Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark ICML 2024
Sparsity-Guided Holistic Explanation for LLMs with Interpretable Inference-Time Intervention AAAI 2024
Molecular Data Programming: Towards Molecule Pseudo-labeling with Systematic Weak Supervision CVPR 2024
TFMQ-DM: Temporal Feature Maintenance Quantization for Diffusion Models CVPR 2024
Contextualization Distillation from Large Language Model for Knowledge Graph Completion EACL 2024
FFN-SkipLLM: A Hidden Gem for Autoregressive Decoding with Adaptive Feed Forward Skipping EMNLP 2024
ReTA: Recursively Thinking Ahead to Improve the Strategic Reasoning of Large Language Models NAACL 2024
Is C4 Dataset Optimal for Pruning? An Investigation of Calibration Data for LLM Pruning EMNLP 2024
DALK: Dynamic Co-Augmentation of LLMs and KG to answer Alzheimer’s Disease Questions with Scientific Literature EMNLP 2024
Two Heads Are Better Than One: Boosting Graph Sparse Training via Semantic and Topological Awareness ICML 2024
Reinforcement Learning-Driven LLM Agent for Automated Attacks on LLMs ACL 2024
Cross-Lingual Multi-Hop Knowledge Editing EMNLP 2024
Facial Affective Behavior Analysis with Instruction Tuning ECCV 2024
Mew: Multiplexed Immunofluorescence Image Analysis through an Efficient Multiplex Network ECCV 2024
Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy ICLR 2024
Sparse MoE with Language Guided Routing for Multilingual Machine Translation ICLR 2024
H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models NIPS 2023
The Emergence of Essential Sparsity in Large Pre-trained Models: The Weights that Matter NIPS 2023
Peeling the Onion: Hierarchical Reduction of Data Redundancy for Efficient Vision Transformer Training AAAI 2023
DSEE: Dually Sparsity-embedded Efficient Tuning of Pre-trained Language Models ACL 2023
Learning to Generalize Provably in Learning to Optimize AISTATS 2023
Enhancing NeRF akin to Enhancing LLMs: Generalizable NeRF Transformer with Mixture-of-View-Experts ICCV 2023
Robust Mixture-of-Expert Training for Convolutional Neural Networks ICCV 2023
AdaMV-MoE: Adaptive Multi-Task Vision Mixture-of-Experts ICCV 2023
M-L2O: Towards Generalizable Learning-to-Optimize by Test-Time Fast Self-Adaptation ICLR 2023
Is Attention All That NeRF Needs? ICLR 2023
More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity ICLR 2023
HotProtein: A Novel Framework for Protein Thermostability Prediction and Editing ICLR 2023
Graph Domain Adaptation via Theory-Grounded Spectral Regularization ICLR 2023
Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together! ICLR 2023
Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers ICLR 2023
Learning to Optimize Differentiable Games ICML 2023
Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate Communication ICML 2023
Instant Soup: Cheap Pruning Ensembles in A Single Pass Can Draw Lottery Tickets from Large Models ICML 2023
Attend Who Is Weak: Pruning-Assisted Medical Image Localization Under Sophisticated and Implicit Imbalances WACV 2023
Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative NIPS 2022
Audio Lottery: Speech Recognition Made Ultra-Lightweight, Noise-Robust, and Transferable ICLR 2022
The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training ICLR 2022
Optimizer Amalgamation ICLR 2022
Unified Visual Transformer Compression ICLR 2022
Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How ICLR 2022
Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic Sparsity ICLR 2022
Symbolic Learning to Optimize: Towards Interpretability and Scalability ICLR 2022
Sparsity Winning Twice: Better Robust Generalization from More Efficient Training ICLR 2022
Anti-Oversmoothing in Deep Vision Transformers via the Fourier Domain Analysis: From Theory to Practice ICLR 2022
Learning Pruning-Friendly Networks via Frank-Wolfe: One-Shot, Any-Sparsity, And No Retraining ICLR 2022
Sandwich Batch Normalization: A Drop-In Replacement for Feature Distribution Heterogeneity WACV 2022
CADTransformer: Panoptic Symbol Spotting Transformer for CAD Drawings CVPR 2022
The Principle of Diversity: Training Stronger Vision Transformers Calls for Reducing All Levels of Redundancy CVPR 2022
Quarantine: Sparsity Can Uncover the Trojan Attack Trigger for Free CVPR 2022
Playing Lottery Tickets with Vision and Language AAAI 2022
Coarsening the Granularity: Towards Structurally Sparse Lottery Tickets ICML 2022
Data-Efficient Double-Win Lottery Tickets from Robust Pre-training ICML 2022
Linearity Grafting: Relaxed Neuron Pruning Helps Certifiable Robustness ICML 2022
Training Your Sparse Neural Network Better with Any Mask ICML 2022
Universality of Winning Tickets: A Renormalization Group Perspective ICML 2022
Neural Implicit Dictionary Learning via Mixture-of-Expert Training ICML 2022
AutoCoG: A Unified Data-Model Co-Search Framework for Graph Neural Networks AUTOML 2022
Randomized Channel Shuffling: Minimal-Overhead Backdoor Attack Detection without Clean Datasets NIPS 2022
MΒ³ViT: Mixture-of-Experts Vision Transformer for Efficient Multi-task Learning with Model-Accelerator Co-design NIPS 2022
Advancing Model Pruning via Bi-level Optimization NIPS 2022
Old can be Gold: Better Gradient Flow can Make Vanilla-GCNs Great Again NIPS 2022
A Comprehensive Study on Large-Scale Graph Training: Benchmarking and Rethinking NIPS 2022
Sparse Winning Tickets are Data-Efficient Image Recognizers NIPS 2022
Scalable Learning to Optimize: A Learned Optimizer Can Train Big Models ECCV 2022
DNA: Improving Few-Shot Transfer Learning with Low-Rank Decomposition and Alignment ECCV 2022
Point Cloud Domain Adaptation via Masked Local 3D Structure Prediction ECCV 2022
Learning to Optimize: A Primer and A Benchmark JMLR 2022
Aug-NeRF: Training Stronger Neural Radiance Fields With Triple-Level Physically-Grounded Augmentations CVPR 2022
Long Live the Lottery: The Existence of Winning Tickets in Lifelong Learning ICLR 2021
Undistillable: Making A Nasty Teacher That CANNOT teach students ICLR 2021
Learning A Minimax Optimizer: A Pilot Study ICLR 2021
Data-Efficient GAN Training Beyond (Just) Augmentations: A Lottery Ticket Perspective NIPS 2021
Robust Overfitting may be mitigated by properly learned smoothening ICLR 2021
Sparse Training via Boosting Pruning Plasticity with Neuroregeneration NIPS 2021
Improving Contrastive Learning on Imbalanced Data via Open-World Sampling NIPS 2021
You are caught stealing my winning lottery ticket! Making a lottery ticket claim its ownership NIPS 2021
GANs Can Play Lottery Tickets Too ICLR 2021
Chasing Sparsity in Vision Transformers: An End-to-End Exploration NIPS 2021
Troubleshooting Blind Image Quality Models in the Wild CVPR 2021
The Lottery Tickets Hypothesis for Supervised and Self-Supervised Pre-Training in Computer Vision Models CVPR 2021
Sanity Checks for Lottery Tickets: Does Your Winning Ticket Really Win the Jackpot? NIPS 2021
A Unified Lottery Ticket Hypothesis for Graph Neural Networks ICML 2021
Self-Damaging Contrastive Learning ICML 2021
Graph Contrastive Learning Automated ICML 2021
Efficient Lottery Ticket Finding: Less Data is More ICML 2021
Sparse and Imperceptible Adversarial Attack via a Homotopy Algorithm ICML 2021
Graph Contrastive Learning with Augmentations NIPS 2020
HALO: Hardware-Aware Learning to Optimize ECCV 2020
Robust Pre-Training by Adversarial Contrastive Learning NIPS 2020
AutoSpeech: Neural Architecture Search for Speaker Recognition INTERSPEECH 2020
Triple Wins: Boosting Accuracy, Robustness and Efficiency Together by Enabling Input-Adaptive Inference ICLR 2020
I Am Going MAD: Maximum Discrepancy Competition for Comparing Classifiers Adaptively ICLR 2020
The Lottery Ticket Hypothesis for Pre-trained BERT Networks NIPS 2020
Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free NIPS 2020
Training Stronger Baselines for Learning to Optimize NIPS 2020
L2-GCN: Layer-Wise and Learned Efficient Training of Graph Convolutional Networks CVPR 2020
Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning CVPR 2020
When Does Self-Supervision Help Graph Convolutional Networks? ICML 2020
Self-PU: Self Boosted and Calibrated Positive-Unlabeled Training ICML 2020
Calibrated Domain-Invariant Learning for Highly Generalizable Large Scale Re-Identification WACV 2020
ABD-Net: Attentive but Diverse Person Re-Identification ICCV 2019
Learning to Optimize in Swarms NIPS 2019