Ming Jin

papers

1,236

total citations

papers (14)

Practical Membership Inference Attacks Against Large-Scale Multi-Modal Models: A Pilot Study

ICCV 2023arXiv

citations

Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting

ICML 2025arXiv

citations

LLMs Can Plan Only If We Tell Them

ICLR 2025arXiv

citations

The Mirrored Influence Hypothesis: Efficient Data Influence Estimation by Harnessing Forward Passes

CVPR 2024arXiv

citations

Tempo Adaptation in Non-stationary Reinforcement Learning

NEURIPS 2023arXiv

citations

Just Enough Shifts: Mitigating Over-Refusal in Aligned Language Models with Targeted Representation Fine-Tuning

ICML 2025arXiv

citations

Can LLMs Correct Themselves? A Benchmark of Self-Correction in LLMs

NEURIPS 2025arXiv

citations

Pausing Policy Learning in Non-stationary Reinforcement Learning

ICML 2024arXiv

citations

Probing Hidden Knowledge Holes in Unlearned LLMs

NEURIPS 2025

citations

Neural Temporal Walks: Motif-Aware Representation Learning on Continuous-Time Dynamic Graphs

NEURIPS 2022

citations

Ming Jin

papers (14)

Time-LLM: Time Series Forecasting by Reprogramming Large Language Models

Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts

Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models

Position: What Can Large Language Models Tell Us about Time Series Analysis

Practical Membership Inference Attacks Against Large-Scale Multi-Modal Models: A Pilot Study

Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting

LLMs Can Plan Only If We Tell Them

The Mirrored Influence Hypothesis: Efficient Data Influence Estimation by Harnessing Forward Passes

Tempo Adaptation in Non-stationary Reinforcement Learning

Just Enough Shifts: Mitigating Over-Refusal in Aligned Language Models with Targeted Representation Fine-Tuning

Can LLMs Correct Themselves? A Benchmark of Self-Correction in LLMs

Pausing Policy Learning in Non-stationary Reinforcement Learning

Probing Hidden Knowledge Holes in Unlearned LLMs

Neural Temporal Walks: Motif-Aware Representation Learning on Continuous-Time Dynamic Graphs

papers (14)

Time-LLM: Time Series Forecasting by Reprogramming Large Language Models

Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts

Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models

Position: What Can Large Language Models Tell Us about Time Series Analysis

Practical Membership Inference Attacks Against Large-Scale Multi-Modal Models: A Pilot Study

Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting

LLMs Can Plan Only If We Tell Them

The Mirrored Influence Hypothesis: Efficient Data Influence Estimation by Harnessing Forward Passes

Tempo Adaptation in Non-stationary Reinforcement Learning

Just Enough Shifts: Mitigating Over-Refusal in Aligned Language Models with Targeted Representation Fine-Tuning

Can LLMs Correct Themselves? A Benchmark of Self-Correction in LLMs

Pausing Policy Learning in Non-stationary Reinforcement Learning

Probing Hidden Knowledge Holes in Unlearned LLMs

Neural Temporal Walks: Motif-Aware Representation Learning on Continuous-Time Dynamic Graphs