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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.CL2025
RandLoRA: Full-rank parameter-efficient fine-tuning of large models
Paul Albert, Frederic Z. Zhang, Hemanth Saratchandran +3
Low-Rank Adaptation (LoRA) and its variants have shown impressive results in reducing the number of trainable parameters and memory requirements of large transformer networks while…