Papers by Jianjun Yu

5 papers
I2E: From Image Pixels to Actionable Interactive Environments for Text-Guided Image Editing (2026.acl-long)

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Challenge: Existing text-guided image editing methods rely on end-to-end pixel-level inpainting paradigm . existing models lack such intermediate representations and Reasoning-then-action process .
Approach: They propose a "Decompose-then-Action" paradigm that revisits image editing as an actionable interaction process within a structured environment.
Outcome: The proposed paradigm outperforms existing methods in compositional editing tasks.
CITE: Benchmarking Heterogeneous Text-Attributed Graph Models (2026.acl-long)

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Challenge: Recent advances in large language models and text-aware graph learning have increased interest in reasoning over text-attributed graphs.
Approach: They propose a large-scale heterogeneous text-attributed graph benchmark for catalytic materials that contains over 438K nodes and 1.2M edges . they establish standardized evaluation protocols for node classification and link prediction and conduct ablation studies to assess the impact of graph heterogenity and textual attributes.
Outcome: The proposed benchmarks are compared to existing methods and provide a baseline for the evaluation of four classes of learning paradigms.
S2ST-Omni: Hierarchical Language-Aware SpeechLLM Adaptation for Multilingual Speech-to-Speech Translation (2026.findings-acl)

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Challenge: S2ST-Omni integrates a speech-to-text frontend with a modular, plug-and-play text-tospeech backend.
Approach: They propose a compositional S2ST framework that integrates a speech-to-text frontend with a modular, plug-and-play text-tospeech backend.
Outcome: The proposed framework outperforms existing frameworks in translation and synthesis . it integrates a speech-to-text translation frontend with a plug-and-play text-tospeech backend .
Takin-VC: Expressive Zero-Shot Voice Conversion via Adaptive Hybrid Content Encoding and Enhanced Timbre Modeling (2025.acl-long)

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Challenge: Expressive zero-shot voice conversion (VC) aims to modify source timbre to match unseen speaker . existing zero- shot VC systems struggle to reproduce paralinguistic information in highly expressive speech .
Approach: They propose a framework for expressive zero-shot voice conversion that uses hybrid content encoding and memory-augmented context-aware timbre modeling.
Outcome: The proposed framework surpasses state-of-the-art VC systems in speech naturalness, speaker similarity, and speaker similarness.
VisKoP: Visual Knowledge oriented Programming for Interactive Knowledge Base Question Answering (2023.acl-demo)

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Challenge: Existing knowledge base question answering systems that parse natural language questions into knowledge oriented program language (KoPL) .
Approach: They propose a knowledge base question answering system that integrates human into the loop to edit and debug queries.
Outcome: The proposed system can debug and edit knowledge base questions on a million-entity-level . it provides auto-completion for its knowledge base schema and user interaction can fix a large portion of wrong KoPL programs to acquire the correct answer.

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