Large Language Model
Semantic Density: Uncertainty Quantification for Large Language Models through Confidence Measurement in Semantic Space
A new framework is proposed in this paper to address these issues.
IaC-Eval: A Code Generation Benchmark for Cloud Infrastructure-as-Code Programs
Infrastructure-as-Code (IaC), an important component of cloud computing, allows the definition of cloud infrastructure in high-level programs.
Learning Where to Edit Vision Transformers Y unqiao Y ang 1 Long-Kai Huang
In this paper, we take initial steps towards correcting predictive errors of ViTs, particularly those arising from subpopulation shifts.
InfoRM: Mitigating Reward Hacking in RLHF via Information-Theoretic Reward Modeling Y uchun Miao
With the advent of large language models (LLMs), reinforcement learning from human feedback (RLHF) has emerged as a pivotal technological paradigm to align models' behaviors with human values [
Meta-Controller: Few-Shot Imitation of Unseen Embodiments and Tasks in Continuous Control
Robot embodiments vary widely in their morphological ( e.g., number and connectivity
Detecting Bugs with Substantial Monetary Consequences by LLM and Rule-based Reasoning
According to a recent study, accounting bugs (i.e., incorrect implementations of domain-specific financial models) are the most prevalent type of vulnerability, and are one of the most difficult to find,
A Practitioner's Guide to Continual Multimodal Pretraining
However, practical model deployment often operates in the gap between these two limit cases, as real-world applications demand adaptation to specific subdomains, tasks or concepts -- spread over the entire, varying life cycle of a model.
Enhancing LLM's Cognition via Structurization
When reading long-form text, human cognition is complex and structurized.