4 citations · 5 across the 18 of their papers we have counts for
18 papers
Stride-k Subsampling: Train-Free Audio Token Reduction for Whisper
Chanhee Cho, Junhyuk Choi, Bugeun Kim
Whisper exposes speech through a fixed 1500-token encoder interface, now a default representation for ASR decoders and Whisper-based speech language models (SpeechLMs), yet its red…
Style as a Confound: False Positives in AI Detection of Non-Native Academic Writing
Hyeonchu Park, Gahye Jeong, Bugeun Kim
AI text detectors are increasingly employed in academic settings, but it remains unclear whether their outputs reflect AI authorship itself or broader linguistic features associate…
Relational Over-Regularization: Graph-Based AI-Generated Text Detection via Sentence Transition Deviation
Hyeonchu Park, Bugeun Kim
Detecting AI-generated text (AIGT) remains challenging because existing approaches rely on token-level statistical signals or independent stylometric features, causing them to over…
VorTEX: Various overlap ratio for Target speech EXtraction
Ro-hoon Oh, Jihwan Seol, Bugeun Kim
Target speech extraction (TSE) aims to recover a target speaker's voice from a mixture. While recent text-prompted approaches have shown promise, most approaches assume fully overl…
Diagnosing the Reliability of LLM-as-a-Judge via Item Response Theory
Junhyuk Choi, Sohhyung Park, Chanhee Cho +2
While LLM-as-a-Judge is widely used in automated evaluation, existing validation practices primarily operate at the level of observed outputs, offering limited insight into whether…
SPAM: Style Prompt Adherence Metric for Prompt-based TTS
Chanhee Cho, Nayeon Kim, Bugeun Kim
Prompt-based text-to-speech (TTS) aims to generate speech that adheres to fine-grained style cues provided in a text prompt. However, most prior works depend on neither plausible n…
Belief in Authority: Impact of Authority in Multi-Agent Evaluation Framework
Junhyuk Choi, Jeongyoun Kwon, Heeju Kim +4
Multi-agent systems utilizing large language models often assign authoritative roles to improve performance, yet the impact of authority bias on agent interactions remains underexp…
Acoustic-based Gender Differentiation in Speech-aware Language Models
Junhyuk Choi, Jihwan Seol, Nayeon Kim +3
Speech-aware Language Models (SpeechLMs) have fundamentally transformed human-AI interaction by enabling voice-based communication, yet they may exhibit acoustic-based gender diffe…
VoiceBBQ: Investigating Effect of Content and Acoustics in Social Bias of Spoken Language Model
Junhyuk Choi, Ro-hoon Oh, Jihwan Seol +1
We introduce VoiceBBQ, a spoken extension of the BBQ (Bias Benchmark for Question Answering) - a dataset that measures social bias by presenting ambiguous or disambiguated contexts…
Pay What LLM Wants: Can LLM Simulate Economics Experiment with 522 Real-human Persona?
Junhyuk Choi, Hyeonchu Park, Haemin Lee +3
Recent advances in Large Language Models (LLMs) have generated significant interest in their capacity to simulate human-like behaviors, yet most studies rely on fictional personas…
MATE: Diagnosing Empathy Calibration Failures in Multi-Turn Human-LLM Interaction
Yeseon Hong, Junhyuk Choi, Minju Kim +1
Large language models are increasingly used in emotionally consequential interactions. Response-level evaluation, however, struggles to diagnose how empathy fails across turns. We…
PHISH in MESH: Korean Adversarial Phonetic Substitution and Phonetic-Semantic Feature Integration Defense
Byungjun Kim, Minju Kim, Hyeonchu Park +1
As malicious users increasingly employ phonetic substitution to evade hate speech detection, researchers have investigated such strategies. However, two key challenges remain. Firs…
A Stereotype Content Analysis on Color-related Social Bias in Large Vision Language Models
Junhyuk Choi, Minju Kim, Yeseon Hong +1
As large vision language models(LVLMs) rapidly advance, concerns about their potential to learn and generate social biases and stereotypes are increasing. Previous studies on LVLM'…
DART: An AIGT Detector using AMR of Rephrased Text
Hyeonchu Park, Byungjun Kim, Bugeun Kim
As large language models (LLMs) generate more human-like texts, concerns about the side effects of AI-generated texts (AIGT) have grown. So, researchers have developed methods for…
Leveraging Large Language Models for Active Merchant Non-player Characters
Byungjun Kim, Minju Kim, Dayeon Seo +1
We highlight two significant issues leading to the passivity of current merchant non-player characters (NPCs): pricing and communication. While immersive interactions with active N…
Examining Identity Drift in Conversations of LLM Agents
Junhyuk Choi, Yeseon Hong, Minju Kim +1
Large Language Models (LLMs) show impressive conversational abilities but sometimes show identity drift problems, where their interaction patterns or styles change over time. As th…
Fine-Grained and Thematic Evaluation of LLMs in Social Deduction Game
Byungjun Kim, Dayeon Seo, Minju Kim +1
Recent studies have investigated whether large language models (LLMs) can support obscured communication, which is characterized by core aspects such as inferring subtext and evadi…
People will agree what I think: Investigating LLM's False Consensus Effect
Junhyuk Choi, Yeseon Hong, Bugeun Kim
Large Language Models (LLMs) have been recently adopted in interactive systems requiring communication. As the false belief in a model can harm the usability of such systems, LLMs…