4 papers
Anchored Self-Play for Code Repair
Caroline Choi, Zeyneb Kaya, Shirley Wu +3
Code repair is an important capability for language models (LMs): given a buggy program and unit tests, an LM must produce a fixed program that passes the tests. Because code repai…
Test-Time Meta-Adaptation with Self-Synthesis
Zeyneb N. Kaya, Nick Rui
As strong general reasoners, large language models (LLMs) encounter diverse domains and tasks, where the ability to adapt and self-improve at test time is valuable. We introduce MA…
The Unified Cognitive Consciousness Theory for Language Models: Anchoring Semantics, Thresholds of Activation, and Emergent Reasoning
Edward Y. Chang, Zeyneb N. Kaya, Ethan Chang
We propose semantic anchoring, a unified account of how large language models turn pretrained capacity into goal-directed behavior: external structure (in-context examples, retriev…
Decoding Large-Language Models: A Systematic Overview of Socio-Technical Impacts, Constraints, and Emerging Questions
Zeyneb N. Kaya, Souvick Ghosh
There have been rapid advancements in the capabilities of large language models (LLMs) in recent years, greatly revolutionizing the field of natural language processing (NLP) and a…