5 papers
DynamixSFT: Dynamic Mixture Optimization of Instruction Tuning Collections
Haebin Shin, Lei Ji, Xiao Liu +4
As numerous instruction-tuning datasets continue to emerge, dynamically balancing and optimizing their mixtures has become a critical challenge. To address this, we propose Dynamix…
Generative Prompt Internalization
Haebin Shin, Lei Ji, Yeyun Gong +3
Prompts used in recent large language model based applications are often fixed and lengthy, leading to significant computational overhead. To address this challenge, we propose Gen…
The BiGGen Bench: A Principled Benchmark for Fine-grained Evaluation of Language Models with Language Models
Seungone Kim, Juyoung Suk, Ji Yong Cho +29
As language models (LMs) become capable of handling a wide range of tasks, their evaluation is becoming as challenging as their development. Most generation benchmarks currently as…
Overcoming Vocabulary Mismatch: Vocabulary-agnostic Teacher Guided Language Modeling
Haebin Shin, Lei Ji, Xiao Liu +1
Using large teacher models to guide the training of smaller student models has become the prevailing paradigm for efficient and effective learning. However, vocabulary mismatches b…
Exploring Adversarial Robustness in Classification tasks using DNA Language Models
Hyunwoo Yoo, Haebin Shin, Kaidi Xu +1
DNA Language Models, such as GROVER, DNABERT2 and the Nucleotide Transformer, operate on DNA sequences that inherently contain sequencing errors, mutations, and laboratory-induced…