Code accompanying Incorporating Chinese Characters of Words for Lexical Sememe Prediction (ACL2018) https://arxiv.org/abs/1806.06349
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Updated
Sep 28, 2018 - Python
Code accompanying Incorporating Chinese Characters of Words for Lexical Sememe Prediction (ACL2018) https://arxiv.org/abs/1806.06349
Multi lingual character based named entity recognizer
Implementation of the Character-level Intra Attention Network (CIAN) for Natural Language Inference (NLI) upon SNLI and MultiNLI corpus
a 5M parameter solution to a problem you could solve by counting on your fingers
LittleLM: A tiny character-level n-gram language model for local corpus building and collaborative experimentation.
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TapeLM: facts as fingerprints on character ink — not token-id memory, not chunk RAG. One frozen curve encoder for generation and structured slot memory (write, bind, hop, resolve). Noisy recall, lexicon calibration, one-shot edits, clean unlearning — vs fair GPT/RAG; reproducible JSON benchmarks.
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A decoder-only GPT built from scratch in pure PyTorch — no nn.Transformer, no HuggingFace. Character-level, writes pseudo-Shakespeare in ~20 min on a laptop CPU. Streaming web playground, 31 tests, every design choice motivated inline.
A simple implementation of a Markov chain text generator that can work at both character and word levels.
Character-level language model series from bigram to WaveNet, with probing analysis of learned phonological representations.
Character-level GPT with six-part attention head analysis — ablation, head patching, residual patching, redundancy testing, seed robustness, and logit lens — converging on one load-bearing head.
SEEM3650 Practical Exam: BabyGPT training with nanoGPT on Shakespeare and open-source Python code, including architecture exploration and code generation samples.
Character-level language model focused on training, architecture, and optimization.
Character-level GPT that generates world place names, trained on GeoNames allCountries — with a live Streamlit demo
On Anonymous Commenting: A Greedy Approach to Balance Utilization and Anonymity for Instagram Users - Accepted at SIGIR 2019
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