Yujia Bao

According to our database1, Yujia Bao authored at least 32 papers between 2017 and 2026.

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Timeline

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Bibliography

2026
Ares: Adaptive Reasoning Effort Selection for Efficient LLM Agents.
CoRR, March, 2026

Adaptive Data Augmentation with Multi-armed Bandit: Sample-Efficient Embedding Calibration for Implicit Pattern Recognition.
CoRR, February, 2026

Observations and Remedies for Large Language Model Bias in Self-Consuming Performative Loop.
CoRR, January, 2026

2025
PromptBridge: Cross-Model Prompt Transfer for Large Language Models.
CoRR, December, 2025

DRAGON: Guard LLM Unlearning in Context via Negative Detection and Reasoning.
CoRR, November, 2025

WebDART: Dynamic Decomposition and Re-planning for Complex Web Tasks.
CoRR, October, 2025

MCP-Bench: Benchmarking Tool-Using LLM Agents with Complex Real-World Tasks via MCP Servers.
CoRR, August, 2025

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models.
CoRR, June, 2025

Advertising in AI systems: Society must be vigilant.
CoRR, May, 2025

Collaborative Memory: Multi-User Memory Sharing in LLM Agents with Dynamic Access Control.
CoRR, May, 2025

Enhancing Retrieval for ESGLLM via ESG-CID - A Disclosure Content Index Finetuning Dataset for Mapping GRI and ESRS.
CoRR, March, 2025

H-CoT: Hijacking the Chain-of-Thought Safety Reasoning Mechanism to Jailbreak Large Reasoning Models, Including OpenAI o1/o3, DeepSeek-R1, and Gemini 2.0 Flash Thinking.
CoRR, February, 2025

Sample, estimate, aggregate: A recipe for causal discovery foundation models.
Trans. Mach. Learn. Res., 2025

KVLink: Accelerating Large Language Models via Efficient KV Cache Reuse.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

LLM Unlearning via Loss Adjustment with Only Forget Data.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

From Isolated Conversations to Hierarchical Schemas: Dynamic Tree Memory Representation for LLMs.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Improving Data Efficiency via Curating LLM-Driven Rating Systems.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Enhancing Retrieval Systems with Inference-Time Logical Reasoning.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2025

2024
LLM Unlearning via Loss Adjustment with Only Forget Data.
CoRR, 2024

Improving Data Efficiency via Curating LLM-Driven Rating Systems.
CoRR, 2024

Harnessing Business and Media Insights with Large Language Models.
CoRR, 2024

Channel Vision Transformers: An Image Is Worth 1 x 16 x 16 Words.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Channel Vision Transformers: An Image Is Worth C x 16 x 16 Words.
CoRR, 2023

Contextual Vision Transformers for Robust Representation Learning.
CoRR, 2023

2022
Efficient and Robust Algorithms for Practical Machine Learning
PhD thesis, 2022

Learning to Split for Automatic Bias Detection.
CoRR, 2022

Learning Stable Classifiers by Transferring Unstable Features.
Proceedings of the International Conference on Machine Learning, 2022

2021
Predict then Interpolate: A Simple Algorithm to Learn Stable Classifiers.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Few-shot Text Classification with Distributional Signatures.
Proceedings of the 8th International Conference on Learning Representations, 2020

2019
Using Machine Learning and Natural Language Processing to Review and Classify the Medical Literature on Cancer Susceptibility Genes.
CoRR, 2019

2018
Deriving Machine Attention from Human Rationales.
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

2017
Hawkes Process Modeling of Adverse Drug Reactions with Longitudinal Observational Data.
Proceedings of the Machine Learning for Healthcare Conference, 2017


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