2 citations · 2 across the 7 of their papers we have counts for
9 papers
The Best Second Opinion Is Right Where the Primary Is Wrong: Partner Selection for Selective Span Tagging
Varun Kotte
A span tagger that ranks its outputs by risk can defer the riskiest ones to a person, and a second model can sharpen this ranking. Which second model should it be? Partner selectio…
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…
Two Wrongs, No Right: Auditing Social-Desirability Bias in LLM Annotators for Computational Social Science
Varun Kotte
LLM annotators are increasingly used in computational social science (CSS), but it is unclear whether their alignment-shaped errors preserve the empirical conclusions a researcher…
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…
Not All Queries Need Rewriting: When Prompt-Only LLM Refinement Helps and Hurts Dense Retrieval
Varun Kotte
Prompt-only, single-step LLM query rewriting, where a rewrite is generated from the query alone without retrieval feedback, is commonly used in production RAG pipelines, but its ef…
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…
Retrieval Augmented Generation for Domain-specific Question Answering
Sanat Sharma, David Seunghyun Yoon, Franck Dernoncourt +5
Question answering (QA) has become an important application in the advanced development of large language models. General pre-trained large language models for question-answering a…