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cs.CL2026
Truth as a Trajectory: What Internal Representations Reveal About Large Language Model Reasoning
Hamed Damirchi, Ignacio Meza De la Jara, Ehsan Abbasnejad +3
Existing explainability methods for Large Language Models (LLMs) typically treat hidden states as static points in activation space, assuming that correct and incorrect inferences…
cs.CL2024
MINI-LLM: Memory-Efficient Structured Pruning for Large Language Models
Hongrong Cheng, Miao Zhang, Javen Qinfeng Shi
As Large Language Models (LLMs) grow dramatically in size, there is an increasing trend in compressing and speeding up these models. Previous studies have highlighted the usefulnes…