Papers by Cuong Pham

2 papers
SpecMind: Cognitively Inspired, Interactive Multi-Turn Framework for Postcondition Inference (2026.acl-long)

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Challenge: Existing methods for generating specifications are limited and often fail to infer semantic specifications such as pre-/postconditions.
Approach: They propose a framework that treats LLMs as exploratory reasoners rather than one-shot generators.
Outcome: The proposed framework outperforms state-of-the-art methods in accuracy and completeness of generated postconditions.
Layer-Wise High-Impact Parameter Ratio Optimization in Post-Training Quantization for Large Language Models (2026.acl-long)

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Challenge: Existing methods to quantize large language models suffer from significant accuracy loss at low bit-widths due to high-impact parameters.
Approach: They propose a quadratic optimization framework that quantizes high-impact parameters to moderate bit-widths while quantizing low bit-wideths.
Outcome: The proposed framework preserves high-impact parameters while preserving memory usage.

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