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Found 6 papers, 4 papers with code
Dictionary Learning Improves Patch-Free Circuit Discovery in Mechanistic Interpretability: A Case Study on Othello-GPT
Sparse dictionary learning has been a rapidly growing technique in mechanistic interpretability to attack superposition and extract more human-understandable features from model activations.
Can AI Assistants Know What They Don't Know?
To answer this question, we construct a model-specific "I don't know" (Idk) dataset for an assistant, which contains its known and unknown questions, based on existing open-domain question answering datasets.
DiffusionBERT: Improving Generative Masked Language Models with Diffusion Models
We present DiffusionBERT, a new generative masked language model based on discrete diffusion models.
Multitask Pre-training of Modular Prompt for Chinese Few-Shot Learning
MP2 is a set of combinable prompts pre-trained on 38 Chinese tasks.
BBTv2: Towards a Gradient-Free Future with Large Language Models
By contrast, gradient-free methods only require the forward computation of the PTM to tune the prompt, retaining the benefits of efficient tuning and deployment.
Generate Point Clouds with Multiscale Details from Graph-Represented Structures
As details are missing in most representations of structures, the lack of controllability to details is one of the major weaknesses in structure-based controllable point cloud generation.
