Papers by Kohei Uehara

2 papers
ToolGrad: Efficient Tool-use Dataset Generation with Textual “Gradients” (2026.findings-acl)

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Challenge: Prior work synthesizes tool-use LLM datasets by first generating a user query, then complex tool-using annotations like DFS.
Approach: They propose an agentic framework that synthesizes user queries and generates valid tool-use chains . they propose a dataset with more complex tool use, lower cost, and almost 100% pass rate .
Outcome: Experiments show that tools trained on ToolGrad outperform expensive baseline datasets and proprietary LLMs.
Content-Specific Humorous Image Captioning Using Incongruity Resolution Chain-of-Thought (2024.findings-naacl)

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Challenge: Existing methods for generating humorous captions are generic and do not capture the content of images.
Approach: They propose a framework that generates content-specific resolutions from fine details extracted from an image and integrates logit bias and negative sampling to suppress the output of generic resolutions.
Outcome: The proposed framework generates humorous captions tailored to the content of specific input images.

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