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cs.CL2024
Towards Interpreting Language Models: A Case Study in Multi-Hop Reasoning
Mansi Sakarvadia
Answering multi-hop reasoning questions requires retrieving and synthesizing information from diverse sources. Language models (LMs) struggle to perform such reasoning consistently…
cs.CL2023★ 3 cited
Attention Lens: A Tool for Mechanistically Interpreting the Attention Head Information Retrieval Mechanism
Mansi Sakarvadia, Arham Khan, Aswathy Ajith +5
Transformer-based Large Language Models (LLMs) are the state-of-the-art for natural language tasks. Recent work has attempted to decode, by reverse engineering the role of linear l…
cs.CL2023★ 1 cited
Memory Injections: Correcting Multi-Hop Reasoning Failures during Inference in Transformer-Based Language Models
Mansi Sakarvadia, Aswathy Ajith, Arham Khan +5
Answering multi-hop reasoning questions requires retrieving and synthesizing information from diverse sources. Large Language Models (LLMs) struggle to perform such reasoning consi…