Dongyeop Kang

Writing is a cognitively demanding activity that requires constant decision-making, heavy reliance on working memory, and frequent shifts between tasks of different goals. To build writing assistants that truly align with writers’ cognition, it is necessary to capture and analyze the complete tho...

Recent Long-Context Language Models (LCLMs) can process hundreds of thousands of tokens in a single prompt, enabling new opportunities for knowledge-intensive multi-hop reasoning by integrating large sets of retrieved documents or, in some cases, directly all necessary information. However, simpl...

Reinforcement fine-tuning improves the reasoning ability of large language models, but it can also encourage them to answer unanswerable queries by guessing or hallucinating missing information. Existing abstention methods either train models to produce generic refusals or encourage follow-up cla...

Large Language Model (LLM) agents can increasingly automate complex reasoning through Test-Time Scaling (TTS), an iterative refinement process guided by reward signals.However, many real-world tasks involve multi-stage pipelines whose final outcomes lack verifiable rewards or sufficient data to t...