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Haokun Li

4 accepted papers

2025

Core Context Aware Transformers for Long Context Language Modeling

ICML 2025poster

Transformer-based Large Language Models (LLMs) have exhibited remarkable success in extensive tasks primarily attributed to self-attention mechanism, which requires a token to consider all preceding tokens as its context to compute attention. However, when the context length L becomes very large (e.…

Cited by 12SourcePDFScholar
2025

From Informal to Formal – Incorporating and Evaluating LLMs on Natural Language Requirements to Verifiable Formal Proofs

ACL 2025long

The research in AI-based formal mathematical reasoning has shown an unstoppable growth trend. These studies have excelled in mathematical competitions like IMO and have made significant progress. However, these studies intertwined multiple skills simultaneously—problem-solving, reasoning, and writin…

2022

Towards Accurate Facial Motion Retargeting with Identity-Consistent and Expression-Exclusive Constraints

AAAI 2022technical

We address the problem of facial motion retargeting that aims to transfer facial motion from a 2D face image to 3D characters. Existing methods often formulate this problem as a 3D face reconstruction problem, which estimates the face attributes such as face identity and expression from face images.…

2020

Generative Low-bitwidth Data Free Quantization

ECCV 2020poster

Neural network quantization is an effective way to compress deep models and improve their execution latency and energy efficiency, so that they can be deployed on mobile or embedded devices. Existingquantization methods require original data for calibration or fine-tuning to get better performance.…