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Technische Universität Berlin
- Berlin
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05:51
(UTC +01:00) - https://qiaw99.github.io/
- in/qianliwang
- @qiaw99.bsky.social
- @qiaw991
Highlights
- Pro
Stars
Repository for XLM-T, a framework for evaluating multilingual language models on Twitter data
A library for mechanistic interpretability of GPT-style language models
A versatile toolkit for applying Logit Lens to modern large language models (LLMs). Currently supports Llama-3.1-8B and Qwen-2.5-7B, enabling layer-wise analysis of hidden states and predictions.
PAIR.withgoogle.com and friend's work on interpretability methods
This is a replicate of DeepSeek-R1-Zero and DeepSeek-R1 training on small models with limited data
Clean, minimal, accessible reproduction of DeepSeek R1-Zero
Scripts for fine-tuning Llama2 via SFT and DPO.
A package to evaluate factuality of long-form generation. Original implementation of our EMNLP 2023 paper "FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation"
FeedbackQA: Improving Question Answering Post-Deployment with Interactive Feedback
A simple and elegant Jekyll theme for an academic personal homepage
Evaluating Cross-lingual Sentence Representations
LLM Transparency Tool (LLM-TT), an open-source interactive toolkit for analyzing internal workings of Transformer-based language models. *Check out demo at* https://huggingface.co/spaces/facebook/l…
Rate, Explain and Cite (REC): Enhanced Explanation and Attribution in Automatic Evaluation by Large Language Models. Paper: https://arxiv.org/pdf/2411.02448
DL Backtrace is a new explainablity technique for deep learning models that works for any modality and model type.
code for EMNLP 2024 paper: Neuron-Level Knowledge Attribution in Large Language Models
ReadMe++: A Multi-domain Multilingual Dataset for Readability Assessment
Easy-to-use MIRAGE code for faithful answer attribution in RAG applications. Paper: https://aclanthology.org/2024.emnlp-main.347/
Public code repo for paper "SaySelf: Teaching LLMs to Express Confidence with Self-Reflective Rationales"
Code for running experiments as well as the dataset DynamicQA
Find and fix bugs in natural language machine learning models using adaptive testing.
User-friendly AI Interface (Supports Ollama, OpenAI API, ...)
Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.
AdalFlow: The library to build & auto-optimize LLM applications.