Hui-Ling Zhen

Efficient Reasoning with Balanced Thinking

PASER: Post-Training Data Selection for Efficient Pruned Large Language Model Recovery

TrimR: Verifier-based Training-Free Thinking Trimming for Efficient Test-Time Scaling

MOSS: Efficient and Accurate FP8 LLM Training with Microscaling and Automatic Scaling

Scaling Up, Speeding Up: A Benchmark of Speculative Decoding for Efficient LLM Test-Time Scaling

Beyond Speedup - Utilizing KV Cache for Sampling and Reasoning

SeedThink: Test-Time Control via Seed-Thought Initialization

Why Attention Patterns Exist: A Unifying Temporal Perspective Analysis

FuseGPT: Prune-and-Fuse Knowledge Redistribution for Efficient Transformers

Analytical Restructuring of Feed-Forward Networks for Accelerated LLM Inference

Harnessing Large Language Models Locally: Empirical Results and Implications

The Graph's Apprentice: Teaching an LLM Low-Level Knowledge for Circuit Quality Estimation

KVTuner: Sensitivity-Aware Layer-Wise Mixed-Precision KV Cache Quantization for Efficient and Nearly Lossless LLM Inference

Searching Strengthens Large Language Models in Finding Bugs of Deep Learning Libraries