1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.CL2026
DepthKV: Layer-Dependent KV Cache Pruning for Long-Context LLM Inference
Zahra Dehghanighobadi, Asja Fischer
Long-context reasoning is a critical capability of large language models (LLMs), enabling applications such as long-document understanding, summarization, and code generation. Howe…
cs.CL2025★ 1 cited
Can LLMs Explain Themselves Counterfactually?
Zahra Dehghanighobadi, Asja Fischer, Muhammad Bilal Zafar
Explanations are an important tool for gaining insights into the behavior of ML models, calibrating user trust and ensuring regulatory compliance. Past few years have seen a flurry…