← Authors

James Zou

97 papers · 2015–2026 · 12 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (11) 🐝 Cross-Pollinator (7) πŸƒ Academic Marathon (10) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (23) 🌈 Renaissance Researcher (9) 🏠 Conference Loyalist (34) 🀝 Dynamic Duo (13) πŸ‘‘ Triple Crown πŸ† Keyword Champion (2) πŸ† Grand Slam πŸ‘₯ Mega-Team (71) πŸ”¬ Deep Specialist (10) 🧬 Topic Evolution πŸ”₯ Unstoppable (11) πŸ“ˆ Trend Setter ⚑ Prolific Year (25) πŸ’Ž Century Club (94) ❓ The Questioner (6) πŸ—ƒοΈ Keyword Collector (66) πŸš€ Conference Pioneer

Conferences

ICML (34) ICLR (21) AISTATS (15) NIPS (11) EMNLP (5) EACL (3) AAAI (2) ACL (2) CVPR (1) ICCV (1) JMLR (1) NAACL (1)

Top co-authors

Linjun Zhang (13) Zhun Deng (7) Yongchan Kwon (7) Mert Yuksekgonul (7) Weixin Liang (7) Haotian Ye (7) Amirata Ghorbani (6) Huaxiu Yao (6) Christopher Re (6) Lingjiao Chen (5)

Keywords

large language model (10) data valuation (6) distribution shift (5) representation learning (5) shapley value (5) false discovery rate (4) question answering (4) data augmentation (4) spurious correlation (4) domain generalization (4) information retrieval (3) contrastive learning (3) feature selection (3) domain adaptation (3) language model (3) semi-supervised learning (2) subpopulation shift (2) feature importance (2) machine learning (2) self-supervised learning (2)

Papers

Dynamic Cheatsheet: Test-Time Learning with Adaptive Memory EACL 2026
Reasoning or Knowledge: Stratified Evaluation of Biomedical LLMs EACL 2026
Science Across Languages: Assessing LLM Multilingual Translation of Scientific Papers EACL 2026
Capturing the Temporal Dependence of Training Data Influence ICLR 2025
Reducing Hallucinations in Large Vision-Language Models via Latent Space Steering ICLR 2025
Mixture-of-Agents Enhances Large Language Model Capabilities ICLR 2025
Locality Alignment Improves Vision-Language Models ICLR 2025
CHORDS: Diffusion Sampling Accelerator with Multi-core Hierarchical ODE Solvers ICCV 2025
Protein Large Language Models: A Comprehensive Survey EMNLP 2025
Inefficiencies of Meta Agents for Agent Design EMNLP 2025
Efficient and Asymptotically Unbiased Constrained Decoding for Large Language Models AISTATS 2025
CollabLLM: From Passive Responders to Active Collaborators ICML 2025
Improving Model Alignment Through Collective Intelligence of Open-Source Models ICML 2025
FactTest: Factuality Testing in Large Language Models with Finite-Sample and Distribution-Free Guarantees ICML 2025
MMed-RAG: Versatile Multimodal RAG System for Medical Vision Language Models ICLR 2025
Cost-efficient Collaboration between On-device and Cloud Language Models ICML 2025
GMValuator: Similarity-based Data Valuation for Generative Models ICLR 2025
MedTrinity-25M: A Large-scale Multimodal Dataset with Multigranular Annotations for Medicine ICLR 2025
SleepFM: Multi-modal Representation Learning for Sleep Across Brain Activity, ECG and Respiratory Signals ICML 2024
GraphMETRO: Mitigating Complex Graph Distribution Shifts via Mixture of Aligned Experts NIPS 2024
UniTox: Leveraging LLMs to Curate a Unified Dataset of Drug-Induced Toxicity from FDA Labels NIPS 2024
TFG: Unified Training-Free Guidance for Diffusion Models NIPS 2024
AvaTaR: Optimizing LLM Agents for Tool Usage via Contrastive Reasoning NIPS 2024
Accelerating Transformers with Spectrum-Preserving Token Merging NIPS 2024
ClashEval: Quantifying the tug-of-war between an LLM’s internal prior and external evidence NIPS 2024
Are More LLM Calls All You Need? Towards the Scaling Properties of Compound AI Systems NIPS 2024
STaRK: Benchmarking LLM Retrieval on Textual and Relational Knowledge Bases NIPS 2024
Enhancing Large Vision Language Models with Self-Training on Image Comprehension NIPS 2024
CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models NIPS 2024
Navigating Dataset Documentations in AI: A Large-Scale Analysis of Dataset Cards on HuggingFace ICLR 2024
DataInf: Efficiently Estimating Data Influence in LoRA-tuned LLMs and Diffusion Models ICLR 2024
Zoology: Measuring and Improving Recall in Efficient Language Models ICLR 2024
Safety-Tuned LLaMAs: Lessons From Improving the Safety of Large Language Models that Follow Instructions ICLR 2024
Simple linear attention language models balance the recall-throughput tradeoff ICML 2024
How Well Can LLMs Negotiate? NegotiationArena Platform and Analysis ICML 2024
Scaling Laws for the Value of Individual Data Points in Machine Learning ICML 2024
Position: TrustLLM: Trustworthiness in Large Language Models ICML 2024
Selecting Large Language Model to Fine-tune via Rectified Scaling Law ICML 2024
Prospector Heads: Generalized Feature Attribution for Large Models & Data ICML 2024
Stochastic Amortization: A Unified Approach to Accelerate Feature and Data Attribution NIPS 2024
ArtWhisperer: A Dataset for Characterizing Human-AI Interactions in Artistic Creations ICML 2024
Rethinking Data Shapley for Data Selection Tasks: Misleads and Merits ICML 2024
Learning and Forgetting Unsafe Examples in Large Language Models ICML 2024
Data-OOB: Out-of-bag Estimate as a Simple and Efficient Data Value ICML 2023
Data-Driven Subgroup Identification for Linear Regression ICML 2023
When and Why Vision-Language Models Behave like Bags-Of-Words, and What to Do About It? ICLR 2023
Post-hoc Concept Bottleneck Models ICLR 2023
The Power of Contrast for Feature Learning: A Theoretical Analysis JMLR 2023
FIFA: Making Fairness More Generalizable in Classifiers Trained on Imbalanced Data ICLR 2023
FaiREE: fair classification with finite-sample and distribution-free guarantee ICLR 2023
HAPI Explorer: Comprehension, Discovery, and Explanation on History of ML APIs AAAI 2023
Diagnosing and Rectifying Vision Models using Language ICLR 2023
Understanding Multimodal Contrastive Learning and Incorporating Unpaired Data AISTATS 2023
Freeze then Train: Towards Provable Representation Learning under Spurious Correlations and Feature Noise AISTATS 2023
Beyond Positive Scaling: How Negation Impacts Scaling Trends of Language Models ACL 2023
Discover and Cure: Concept-aware Mitigation of Spurious Correlation ICML 2023
Accuracy on the Curve: On the Nonlinear Correlation of ML Performance Between Data Subpopulations ICML 2023
How to Learn when Data Gradually Reacts to Your Model AISTATS 2022
MLDemon:Deployment Monitoring for Machine Learning Systems AISTATS 2022
Meaningfully debugging model mistakes using conceptual counterfactual explanations ICML 2022
Efficient Online ML API Selection for Multi-Label Classification Tasks ICML 2022
Improving Out-of-Distribution Robustness via Selective Augmentation ICML 2022
When and How Mixup Improves Calibration ICML 2022
Clustering Plotted Data by Image Segmentation CVPR 2022
SEAL: Interactive Tool for Systematic Error Analysis and Labeling EMNLP 2022
Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning AISTATS 2022
How Did the Model Change? Efficiently Assessing Machine Learning API Shifts ICLR 2022
MetaShift: A Dataset of Datasets for Evaluating Contextual Distribution Shifts and Training Conflicts ICLR 2022
Domino: Discovering Systematic Errors with Cross-Modal Embeddings ICLR 2022
How to Learn when Data Reacts to Your Model: Performative Gradient Descent ICML 2021
How Does Mixup Help With Robustness and Generalization? ICLR 2021
Improving Adversarial Robustness via Unlabeled Out-of-Domain Data AISTATS 2021
Efficient Computation and Analysis of Distributional Shapley Values AISTATS 2021
Competing AI: How does competition feedback affect machine learning? AISTATS 2021
Approximate Data Deletion from Machine Learning Models AISTATS 2021
Improving Generalization in Meta-learning via Task Augmentation ICML 2021
ALICE: Active Learning with Contrastive Natural Language Explanations EMNLP 2020
Beyond User Self-Reported Likert Scale Ratings: A Comparison Model for Automatic Dialog Evaluation ACL 2020
A Distributional Framework For Data Valuation ICML 2020
Learning transport cost from subset correspondence ICLR 2020
Explaining the Trump Gap in Social Distancing Using COVID Discourse EMNLP 2020
Knockoffs for the Mass: New Feature Importance Statistics with False Discovery Guarantees AISTATS 2019
Discovering Conditionally Salient Features with Statistical Guarantees ICML 2019
Interpretation of Neural Networks Is Fragile AAAI 2019
Adaptive Monte Carlo Multiple Testing via Multi-Armed Bandits ICML 2019
Concrete Autoencoders: Differentiable Feature Selection and Reconstruction ICML 2019
Data Shapley: Equitable Valuation of Data for Machine Learning ICML 2019
Analyzing Polarization in Social Media: Method and Application to Tweets on 21 Mass Shootings NAACL 2019
Improving the Stability of the Knockoff Procedure: Multiple Simultaneous Knockoffs and Entropy Maximization AISTATS 2019
Why Adaptively Collected Data Have Negative Bias and How to Correct for It AISTATS 2018
CoVeR: Learning Covariate-Specific Vector Representations with Tensor Decompositions ICML 2018
Learning Latent Space Models with Angular Constraints ICML 2017
Quantifying the accuracy of approximate diffusions and Markov chains AISTATS 2017
Estimating the unseen from multiple populations ICML 2017
Rich Component Analysis ICML 2016
Controlling Bias in Adaptive Data Analysis Using Information Theory AISTATS 2016
Intersecting Faces: Non-negative Matrix Factorization With New Guarantees ICML 2015