Papers with static approaches

2 papers
Adaptive Weighted Proxy Tuning: Efficient Gray-Box Steering for Image Captioning. (2026.acl-industry)

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Challenge: Proxy tuning is a decoding-time approach that fails to account for instance-specific variations in model certainty and domain shift.
Approach: They propose a gray-box steering framework that dynamically modulates the logit contributions of a large base model, a fine-tuned expert, and an untune .
Outcome: Adaptive Weighted Proxy Tuning achieves performance parity with fine-tuned models while remaining parameter-free.
Conversational Semantic Parsing using Dynamic Context Graphs (2023.emnlp-main)

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Challenge: Existing work on conversational semantic parsing has focused on answering questions in isolation . whereas existing work on KBQA is focused on resolving questions in the context of natural language questions .
Approach: They propose to model conversational semantic parsing over general purpose knowledge graphs with millions of entities and thousands of relation-types by exploiting its underlying structure and encoding it with a graph neural network.
Outcome: The proposed model is better at processing discourse information and longer interactions . it is better than static models at handling ellipsis and coreference, the authors show .

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