Enforcing Grammar in Code Synthesis with Transformers

In this work, we present the grammar enforcement method, which introduces a separate layer that constrains the decisions of the transformer during fine-tuning.

Enforcing Grammar in Code Synthesis with Transformers. Dmytro Vitel, Stephen Steinle, John Licato. University of South Florida. 4202 E Fowler Ave, Tampa, FL ...

(PDF) Enforcing Grammar in Code Synthesis with Transformers

In this work, we present the grammar enforcement method, which introduces a separate layer that constrains the decisions of the transformer during fine-tuning ...

[PDF] Enforcing Grammar in Code Synthesis with Transformers ...

This work presents the grammar enforcement method, which introduces a separate layer that constrains the decisions of the transformer during fine-tuning ...

Enforcing Grammar in Code Synthesis with Transformers

Enforcing Grammar in Code Synthesis with Transformers. Computer Science · Physics · Philosophy. Show More. Authors. Dmytro Vitel,Stephen Steinle. ,John Licato.

How ensure natural language transformers, like GPT-3, a correct ...

When using natural language transformers, like GPT-3, to produce text, we need to ensure that the grammar it is using is correct.

Transformer-Based Models Are Not Yet Perfect At Learning to ... - arXiv

Our framework supports syntax by way of a new sequential encoding (Section 3) based on inductive representations of recursively defined ...

pszemraj/bart-base-grammar-synthesis - Hugging Face

The corrector pipeline is initialized with the "pszemraj/bart-base-grammar-synthesis" model, which is designed for grammar correction. The ...

Augmenting Transformer Language Models with Syntactic Inductive ...

Transformer Grammars (TGs) achieve better (i) single-sentence language modeling perplexity, (ii) syntactic generalization, and (iii) parse ...

Transformers are uninterpretable with myopic methods: a case study...

Lastly, they conduct experiments with Transformers trained on bounded Dyck languages. They compare the attention patterns of trained Transformers with different ...

Improving LLM Code Generation with Grammar Augmentation - arXiv

The results underscore the significant reduction of 96.07% of syntax errors achieved when SynCode is combined with state-of-the-art LLMs, ...

Improving Transformer Based End-to-End Code-Switching Speech ...

CTC helps the Transformer to converge with the forward–backward algorithm, enforcing a monotonic alignment between input features and output labels. The ...

Program Synthesis using Abstraction Refinement

(1) (s0 = [Π]ein) ⇒ ψ where s0 is the start symbol of the grammar,. (2) φ ∧ψ ⇒ (s0 , eout). Proceedings of the ACM on Programming Languages, Vol. 2, No. POPL, ...

Leveraging pre-trained language models for code generation

Finally, programming from Description using Rich Domain-Specific Languages. Semantic parsing methods like Neural Program Search [56] and ...

ATISS: Autoregressive Transformers for Indoor Scene Synthesis

Meta-Sim [23] learned a model that modifies attributes of scene graphs sampled from a known probabilistic context-free grammar to match visual statistics ...

Sparse Format Conversion and Code Synthesis

Enforce array property procedure is detailed in Algorithm 3. The components of the ufProperty include the domain, range, and array properties. Figure 4.3 shows.

pszemraj/grammar-synthesis-large - Hugging Face

The intent is to create a text2text language model that successfully completes "single-shot grammar correction" on a potentially grammatically ...

An Empirical Study of Code Smells in Transformer-based Code ...

This partial code has been taken from the APPS dataset [25] where at line 12, the assert is used to enforce the value of the variable diff is greater than or ...

The grammar lab as teaching and learning sequence based on ...

Enforcing Grammar in Code Synthesis with Transformers. Article. Full-text available. May 2023. Dmytro Vitel · Stephen Steinle ...

guidance-ai/guidance: A guidance language for controlling ... - GitHub

While constrained_ner(input) is a grammar that constrains the model generation, it feels like you're just writing normal imperative python code with += and ...