Yada Zhu
22 papers · 2018–2026 · 10 conferences · across top CS/AI conferences
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🐝 Cross-Pollinator (12) 🌉 Interdisciplinary Bridge 🌍 Conference Polyglot (9) 🏃 Academic Marathon (7) 🌈 Renaissance Researcher (8)
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Conferences
AAAI (4)
ACL (4)
ICLR (3)
ICML (3)
IJCAI (2)
NAACL (2)
EACL (1)
EMNLP (1)
IJCNLP (1)
NIPS (1)
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Research topics
Keywords
large language model
(3)
influence function
(3)
graph representation learning
(2)
semantic evaluation
(2)
sample-based explanation
(2)
node classification
(2)
random walk
(2)
model faithfulness
(2)
hessian-free method
(2)
link prediction
(1)
mathematical reasoning
(1)
graph classification
(1)
self-supervised learning
(1)
zero-shot learning
(1)
neural tangent kernel
(1)
parameter estimation
(1)
instruction tuning
(1)
text classification
(1)
reinforcement learning
(1)
community detection
(1)
Papers
UniToolBench: A Benchmark for Tool-Augmented LLMs in Cross-Domain, Universal Task Automation
EACL 2026
Mem-Gallery: Benchmarking Multimodal Long-Term Conversational Memory for MLLM Agents
ACL 2026
Reasoning of Large Language Models over Knowledge Graphs with Super-Relations
ICLR 2025
PLAY2PROMPT: Zero-shot Tool Instruction Optimization for LLM Agents via Tool Play
ACL 2025
Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting
ICML 2025
Evaluating Large Language Models with Enterprise Benchmarks
NAACL 2025
Sterling: Synergistic Representation Learning on Bipartite Graphs
AAAI 2024
Self-Specialization: Uncovering Latent Expertise within Large Language Models
ACL 2024
Paraphrase and Solve: Exploring and Exploiting the Impact of Surface Form on Mathematical Reasoning in Large Language Models
NAACL 2024
Neural Active Learning Beyond Bandits
ICLR 2024
Adversarial Attacks on Fairness of Graph Neural Networks
ICLR 2024
Temporal Graph Neural Tangent Kernel with Graphon-Guaranteed
NIPS 2024
Class-Imbalanced Graph Learning without Class Rebalancing
ICML 2024
Learning Optimal Projection for Forecast Reconciliation of Hierarchical Time Series
ICML 2024
Stock Price Volatility Prediction: A Case Study with AutoML
EMNLP 2022
On Sample Based Explanation Methods for NLP: Faithfulness, Efficiency and Semantic Evaluation
ACL 2021
On Sample Based Explanation Methods for NLP: Faithfulness, Efficiency and Semantic Evaluation
IJCNLP 2021
Outlier Impact Characterization for Time Series Data
AAAI 2021
Reinforcement-Learning Based Portfolio Management with Augmented Asset Movement Prediction States
AAAI 2020
Task-Based Learning via Task-Oriented Prediction Network with Applications in Finance
IJCAI 2020
Towards Fine-Grained Temporal Network Representation via Time-Reinforced Random Walk
AAAI 2020
A Local Algorithm for Product Return Prediction in E-Commerce
IJCAI 2018