Papers with DFG

2 papers
Multimodal Language Analysis in the Wild: CMU-MOSEI Dataset and Interpretable Dynamic Fusion Graph (P18-1)

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Challenge: Analyzing human multimodal language is emerging area of research in NLP.
Approach: They propose a multimodal fusion technique to exploit how modalities interact in multimodal language.
Outcome: The proposed technique exploits how modalities interact with each other in human multimodal language.
SLICEFORMER: Static Program Slicing Using Language Models With Dataflow-Aware Pretraining and Constrained Decoding (2026.acl-long)

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Challenge: Static program slicing is a software engineering technique for isolating code relevant to specific variables.
Approach: They propose a new approach that reformulates static program slicing as a sequence-to-sequence task using small language models such as CodeT5+.
Outcome: The proposed approach improves on Java and Python program slicing benchmarks with up to 22% gain in ExactMatch.

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