Papers by Weixiang Zhou

3 papers
ConsistentChat: Building Skeleton-Guided Consistent Multi-Turn Dialogues for Large Language Models from Scratch (2025.emnlp-main)

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Challenge: Existing instruction data synthesis methods focus on single-turn instructions and neglect cross-turn coherence, resulting in context drift and reduced task completion rates.
Approach: They propose a framework that constrains multi-turn instruction synthesis by explicitly modeling human conversational intent.
Outcome: The proposed framework outperforms existing models trained on single-turn and multi-turn instruction datasets.
Expanding the Boundaries of Vision Prior Knowledge in Multi-modal Large Language Models (2026.eacl-long)

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Challenge: Existing research treats MLLMs as unified systems optimized through end-to-end training, but the impact of vision encoder’s prior knowledge is seldom investigated.
Approach: They propose a metric to quantify the effect of prior knowledge on MLLM performance by integrating prior knowledge at the vision encoder level into a training framework.
Outcome: The proposed training framework incorporates prior knowledge at the vision encoder level, and significantly boosts visual understanding capabilities of MLLMs.
PPTAgent: Generating and Evaluating Presentations Beyond Text-to-Slides (2025.emnlp-main)

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Challenge: Existing methods for generating presentations from documents focus on improving and evaluating content quality in isolation, overlooking visual appeal and structural coherence.
Approach: They propose an edit-based presentation generation system that analyzes and iterates on slides to create new slides.
Outcome: The proposed presentation generation tool outperforms existing methods in three dimensions . it analyzes slides, iterates and generates edit actions based on selected slides .

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