Sentiment Analysis Framework for Researcher with Pytorch
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Updated
Nov 28, 2022 - Python
Sentiment Analysis Framework for Researcher with Pytorch
Offline Federated RL for O-RAN slice resource management on Colosseum traces
DSPy framework for detecting and preventing safety override cascades in LLM systems. Research-grade implementation for studying when completion urgency overrides safety constraints.
A lightweight Python library for reproducible computational experiments with an ultra-simple, smart API. From idea to insight in under 5 minutes, with zero configuration.
A research framework for implementing and evaluating poisoning attacks on Retrieval-Augmented Generation (RAG) systems, enabling the study of their security vulnerabilities.
CrucibleFramework: A scientific platform for LLM reliability research on the BEAM
Modular PyTorch lab for running configurable deep-learning experiments, with ready-to-use data loaders, training pipelines, and metric tracking for both vision and NLP benchmarks.
🌐 Detect and prevent safety overrides in LLM systems with this DSPy-based framework, ensuring actions align with safety constraints.
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