Tianlong Chen

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Approach AAAI 2025 Breaking the Resource Monopoly from Industries: Sustainable and Reliable LLM Serving by Recycling Outdated and Resource-Constrained GPUs AAAI 2025 In Prospect and Retrospect: Reflective Memory Management for Long-term Personalized Dialogue Agents ACL 2025 SCALE: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 M³ViT: 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