72 citations · 330 across the 48 of their papers we have counts for
10 papers · 1 filter
Lost in the Prompt Order: Revealing the Limitations of Causal Attention in Language Models
Hyunjong Ok, Jaeho Lee
Large language models exhibit surprising sensitivity to the structure of the prompt, but the mechanisms underlying this sensitivity remain poorly understood. In this work, we condu…
AuditoryBench++: Can Language Models Understand Auditory Knowledge without Hearing?
Hyunjong Ok, Suho Yoo, Hyeonjun Kim +1
Even without directly hearing sounds, humans can effortlessly reason about auditory properties, such as pitch, loudness, or sound-source associations, drawing on auditory commonsen…
Speculative End-Turn Detector for Efficient Speech Chatbot Assistant
Hyunjong Ok, Suho Yoo, Jaeho Lee
Spoken dialogue systems powered by large language models have demonstrated remarkable abilities in understanding human speech and generating appropriate spoken responses. However,…
Imagine to Hear: Auditory Knowledge Generation can be an Effective Assistant for Language Models
Suho Yoo, Hyunjong Ok, Jaeho Lee
Language models pretrained on text-only corpora often struggle with tasks that require auditory commonsense knowledge. Previous work addresses this problem by augmenting the langua…
Prompt-based Depth Pruning of Large Language Models
Juyun Wee, Minjae Park, Jaeho Lee
Depth pruning aims to reduce the inference cost of a large language model without any hardware-specific complications, by simply removing several less important transformer blocks.…
S2Cap: A Benchmark and a Baseline for Singing Style Captioning
Hyunjong Ok, Jaeho Lee
Singing voices contain much richer information than common voices, including varied vocal and acoustic properties. However, current open-source audio-text datasets for singing voic…
AudioBERT: Audio Knowledge Augmented Language Model
Hyunjong Ok, Suho Yoo, Jaeho Lee
Recent studies have identified that language models, pretrained on text-only datasets, often lack elementary visual knowledge, \textit{e.g.,} colors of everyday objects. Motivated…
Decoding with Limited Teacher Supervision Requires Understanding When to Trust the Teacher
Hyunjong Ok, Jegwang Ryu, Jaeho Lee
How can small-scale large language models (LLMs) efficiently utilize the supervision of LLMs to improve their generative quality? This question has been well studied in scenarios w…
Rethinking Pruning Large Language Models: Benefits and Pitfalls of Reconstruction Error Minimization
Sungbin Shin, Wonpyo Park, Jaeho Lee +1
This work suggests fundamentally rethinking the current practice of pruning large language models (LLMs). The way it is done is by divide and conquer: split the model into submodel…
SCANNER: Knowledge-Enhanced Approach for Robust Multi-modal Named Entity Recognition of Unseen Entities
Hyunjong Ok, Taeho Kil, Sukmin Seo +1
Recent advances in named entity recognition (NER) have pushed the boundary of the task to incorporate visual signals, leading to many variants, including multi-modal NER (MNER) or…