Faithful and Fast Influence Function via Advanced Sampling
arXiv:2510.26776v2 Announce Type: replace-cross Abstract: How can we explain the influence of training data on black-box models? Influence functions (IFs)…
For An Exciting Tomorrow
arXiv:2510.26776v2 Announce Type: replace-cross Abstract: How can we explain the influence of training data on black-box models? Influence functions (IFs)…
arXiv:2510.26852v1 Announce Type: new Abstract: Large Language Model (LLM) agents have evolved from basic text generation to autonomously completing complex…
arXiv:2510.25366v2 Announce Type: replace-cross Abstract: The key task of machine learning is to minimize the loss function that measures the…
arXiv:2510.26451v1 Announce Type: cross Abstract: Graph condensation (GC) has gained significant attention for its ability to synthesize smaller yet informative…
arXiv:2510.26457v1 Announce Type: cross Abstract: Identifying and addressing security issues during the early phase of the development lifecycle is critical…
arXiv:2510.25744v2 Announce Type: replace-cross Abstract: Current evaluations of agents remain centered around one-shot task completion, failing to account for the…
arXiv:2510.25775v1 Announce Type: new Abstract: Contemporary chess engines offer precise yet opaque evaluations, typically expressed as centipawn scores. While effective…