Papers with context grounding
Enhancing Contextual Understanding in Large Language Models through Contrastive Decoding (2024.naacl-long)
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| Challenge: | Large language models lack contextual knowledge, resulting in text with factual inconsistencies or contextually unfaithful content. |
| Approach: | They propose a method that integrates contrastive decoding with adversarial irrelevant passages as negative samples to enhance robust context grounding during generation. |
| Outcome: | The proposed method improves context grounding during generation without training. |
Understanding and Leveraging the Expert Specialization of Context Faithfulness in Mixture-of-Experts LLMs (2025.emnlp-main)
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| Challenge: | Context faithfulness is essential for reliable reasoning in context-dependent scenarios. |
| Approach: | They propose a method that identifies and fine-tunes context-faithful experts . they propose 'context-faither fine- tuning' which selectively fine- tunes them . |
| Outcome: | The proposed method identifies experts with specialization in context utilization and improves context grounding. |
Towards Dog Bark Decoding: Leveraging Human Speech Processing for Automated Bark Classification (2024.lrec-main)
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| Challenge: | Similar to humans, animals make extensive use of verbal and non-verbal forms of communication, including audio signals. |
| Approach: | They propose to use self-supervised speech representation models pre-trained on human speech to address dog bark classification tasks. |
| Outcome: | The proposed model improves dog recognition, breed identification, gender classification, and context grounding tasks. |