Papers by Tianbo Ji
Semantic-Aware Dynamic Retrospective-Prospective Reasoning for Event-Level Video Question Answering (2023.acl-srw)
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| Challenge: | Event-Level Video Question Answering (EVQA) requires complex reasoning across video events to obtain the visual information needed to provide optimal answers. |
| Approach: | They propose a semantic-aware dynamic retrospective-prospective reasoning approach for video-based question answering that explicitly uses the Semantic Role Labeling (SRL) structure of the question in the dynamic reasoning process. |
| Outcome: | The proposed model outperforms existing models on a trafficQA benchmark dataset. |
Document-Level Machine Translation with Large Language Models (2023.emnlp-main)
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| Challenge: | Large language models (LLMs) such as ChatGPT can produce coherent, cohesive, relevant, and fluent answers for various natural language processing tasks. |
| Approach: | They examine the impact of different prompts on document-level translation quality and discourse phenomena using figures and lines, which are invisible to GPT-4. |
| Outcome: | The proposed models outperform commercial MT systems and advanced document-level MT methods on a number of benchmarks and show potential to become a new paradigm for document- level translation. |
Achieving Reliable Human Assessment of Open-Domain Dialogue Systems (2022.acl-long)
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| Challenge: | Evaluation of open-domain dialogue systems is challenging and unreliable . human evaluation of live conversations is highly reliable, but reliability cannot be assumed . |
| Approach: | They propose a method of open-domain dialogue evaluation that is highly reliable . they compare live conversations with models that avoid pre-created reference dialogues . |
| Outcome: | The proposed method is highly reliable while remaining feasible and low cost. |