Papers by Lianghao Deng

2 papers
MuKA: Multimodal Knowledge Augmented Visual Information-Seeking (2025.coling-main)

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Challenge: Existing methods for visual information-seeking tasks rely on textual knowledge . existing methods can impair information retrieval and confuse MLLMs .
Approach: They propose a framework which leverages a multimodal knowledge base to address these limitations.
Outcome: The proposed framework outperforms state-of-the-art methods on the InfoSeek and E-VQA benchmarks.
DeepPlanning: Benchmarking Long-Horizon Agentic Planning with Verifiable Constraints (2026.acl-long)

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Challenge: Existing LLM planning benchmarks emphasize local, step-level reasoning rather than global constrained optimization.
Approach: They propose a benchmark for practical long-horizon agent planning that uses local constrained reasoning and global constrained optimization.
Outcome: The proposed benchmarks show that even frontier agentic LLMs struggle with these problems.

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