2 citations · 2 across the 7 of their papers we have counts for
5 papers · 1 filter
Softmax Reparameterization for Output-Head Quantization
Asim Kadav, Christian Flores, Chirag Arora +5
Large vocabularies make output heads a substantial inference cost in small language models. We introduce softmax reparameterization, a post-training method that searches over funct…
When Can Conformal Risk Control Certify LLM Outputs? Bounds, Impossibility, and Adaptation for Structured Generation
Varun Kotte
Large language models (LLMs) deployed for structured generation (NER, JSON extraction, QA, and classification) lack formal reliability guarantees, and standard heuristic abstention…
PASC: Pipeline-Aware Conformal Prediction with Joint Coverage Guarantees for Multi-Stage NLP and LLM Pipelines
Varun Kotte
Modern NLP and LLM systems are pipelines: named entity recognition (NER) -> entity disambiguation (NED) -> entity typing, retrieval-augmented generation (retriever -> reader), and…
UCCI: Calibrated Uncertainty for Cost-Optimal LLM Cascade Routing
Varun Kotte
LLM cascades and model routing promise lower inference cost by sending easy queries to a small model and escalating hard ones to a large model, but most deployed routers use uncali…
PromptPort: A Reliability Layer for Cross-Model Structured Extraction
Varun Kotte
Structured extraction with LLMs fails in production not because models lack understanding, but because output formatting is unreliable across models and prompts. A prompt that retu…