Papers with TG

2 papers
Enhancing Temporal Modeling of Video LLMs via Time Gating (2024.findings-emnlp)

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Challenge: Existing Video Large Language Models neglect temporal information in video data, leading to struggles with temporal-aware video understanding.
Approach: They propose a Time Gating Video LLM (TG-Vid) that employs a time gating module to enhance temporal modeling.
Outcome: The proposed model outperforms existing Large Language Models on video-and-language tasks and ablation studies show that the model outpersforms the existing models.
If Attention Serves as a Cognitive Model of Human Memory Retrieval, What is the Plausible Memory Representation? (2025.acl-long)

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Challenge: Recent work in computational psycholinguistics has revealed intriguing parallels between attention mechanisms and human memory retrieval, focusing primarily on vanilla Transformers that operate on token-level representations.
Approach: They propose that the attention mechanism of Transformer Grammar (TG) can serve as a cognitive model of human memory retrieval using Normalized Attention Entropy (NAE) they propose that TG's attention can implement a human memory-retrieval theory known as cue-based retrieval .
Outcome: The attention mechanism of Transformer Grammar (TG) achieves superior predictive power for self-paced reading times compared to vanilla Transformer’s, with further analyses revealing independent contributions from both models.

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