Publications (8)
Semantic Sentence Matching with Densely-connected Recurrent and Co-attentive Information
Seonhoon Kim, Inho Kang, Nojun Kwak
Sentence matching is widely used in various natural language tasks such as natural language inference, paraphrase identification, and question answering. For these tasks, understan…
A Versatile Framework for Evaluating Ranked Lists in terms of Group Fairness and Relevance
Tetsuya Sakai, Jin Young Kim, Inho Kang
We present a simple and versatile framework for evaluating ranked lists in terms of group fairness and relevance, where the groups (i.e., possible attribute values) can be either n…
From Relevance to Authority: Authority-aware Generative Retrieval in Web Search Engines
Sunkyung Lee, Jihye Back, Donghyeon Jeon +4
Generative information retrieval (GenIR) formulates the retrieval process as a text-to-text generation task, leveraging the vast knowledge of large language models. However, existi…
SLM as Guardian: Pioneering AI Safety with Small Language Models
Ohjoon Kwon, Donghyeon Jeon, Nayoung Choi +6
Most prior safety research of large language models (LLMs) has focused on enhancing the alignment of LLMs to better suit the safety requirements of humans. However, internalizing s…
What Changes Can Large-scale Language Models Bring? Intensive Study on HyperCLOVA: Billions-scale Korean Generative Pretrained Transformers
Boseop Kim, HyoungSeok Kim, Sang-Woo Lee +34
GPT-3 shows remarkable in-context learning ability of large-scale language models (LMs) trained on hundreds of billion scale data. Here we address some remaining issues less report…
ROSAQ: Rotation-based Saliency-Aware Weight Quantization for Efficiently Compressing Large Language Models
Junho Yoon, Geom Lee, Donghyeon Jeon +2
Quantization has been widely studied as an effective technique for reducing the memory requirement of large language models (LLMs), potentially improving the latency time as well.…