21 citations · 25 across the 16 of their papers we have counts for
8 papers · 1 filter
Is Discrete Difficulty Sufficient? Leveraging Continuous Difficulty for Efficient Self-Consistency in LLMs
Sihyeong Yeom, Geon Park, Geunyeong Jeong +3
Self-Consistency (SC) is a decoding strategy that samples diverse reasoning paths and selects the most consistent answer, demonstrating strong performance on complex reasoning prob…
GRASP: GRanularity-Aware Search Policy for Agentic RAG
Varun Gandhi, Jaewook Lee, Shantanu Todmal +4
Agentic retrieval-augmented generation (RAG) extends static RAG by allowing language models to iteratively reason, generate search queries, retrieve evidence, and predict answers.…
Beyond Attack Success Rate: Temporal Logit Observability for LLM Safety Failures
Junyoung Park, Sunghwan Park, Seongyong Ju +1
Attack Success Rate (ASR) evaluates each jailbreak with a single yes/no label at the end of generation, telling us whether a failure happened but not how it unfolded. Two attacks t…
Who Am I? History-Aware Profiles for Student Simulation in Tutoring Dialogues
Zhangqi Duan, Shuyan Huang, Alexander Scarlatos +3
A key part of developing large language model (LLM)-powered, automated tutoring tools is student simulation, i.e., using LLMs to role-play as students, which can facilitate tutor m…
Interpretable Difficulty-Aware Knowledge Tracing in Tutor-Student Dialogues
Shuyan Huang, Alexander Scarlatos, Jaewook Lee +1
Recent advances in large language models (LLMs) have led to the development of AI-powered tutoring systems that provide interactive support via dialogue. To enable these tutoring s…
Interrogating Design Homogenization in Web Vibe Coding
Donghoon Shin, Alice Gao, Rock Yuren Pang +3
Generative AI is known for its tendency to homogenize, often reproducing dominant style conventions found in training data. However, it remains unclear how these homogenizing effec…
Letting Tutor Personas Speak Up for LLMs: Learning Steering Vectors from Dialogue via Preference Optimization
Jaewook Lee, Alexander Scarlatos, Simon Woodhead +1
With the emergence of large language models (LLMs) as a powerful class of generative artificial intelligence (AI), their use in tutoring has become increasingly prominent. Prior wo…
Simulated Students in Tutoring Dialogues: Substance or Illusion?
Alexander Scarlatos, Jaewook Lee, Simon Woodhead +1
Advances in large language models (LLMs) enable many new innovations in education. However, evaluating the effectiveness of new technology requires real students, which is time-con…