Papers by Wonjong Rhee

2 papers
Soft Head Selection for Injecting ICL-Derived Task Embeddings (2026.findings-acl)

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Challenge: Large language models (LLMs) are commonly adapted to downstream tasks using parameter-efficient fine-tuning (PEFT) or in-context learning (ICL).
Approach: They propose a gradient-based method that derives task-specific embeddings from activations using few-shot prompts and injects them during inference.
Outcome: The proposed method outperforms existing methods on open-ended generation, reasoning, and natural language understanding tasks while using fewer trainable parameters.
Progressive Multimodal Search and Reasoning for Knowledge-Intensive Visual Question Answering (2026.acl-long)

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Challenge: Existing approaches to knowledge-intensive visual question answering lack mechanisms to revise misdirected reasoning.
Approach: They propose a framework that progressively constructs a structured reasoning trajectory . they use dual-scope queries to retrieve diverse knowledge from heterogeneous knowledge bases .
Outcome: The proposed framework improves retrieval recall and end-to-end answer accuracy.

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