39 citations · 99 across the 6 of their papers we have counts for
6 papers
ExtractBench: A Benchmark and Evaluation Methodology for Complex Structured Extraction
Nick Ferguson, Josh Pennington, Narek Beghian +4
Unstructured documents like PDFs contain valuable structured information, but downstream systems require this data in reliable, standardized formats. LLMs are increasingly deployed…
BlitzRank: Principled Zero-shot Ranking Agents with Tournament Graphs
Sheshansh Agrawal, Thien Hang Nguyen, Douwe Kiela
Selecting the top from items via expensive -wise comparisons is central to settings ranging from LLM-based document reranking to crowdsourced evaluation and tournament d…
OOD-DiskANN: Efficient and Scalable Graph ANNS for Out-of-Distribution Queries
Shikhar Jaiswal, Ravishankar Krishnaswamy, Ankit Garg +2
State-of-the-art algorithms for Approximate Nearest Neighbor Search (ANNS) such as DiskANN, FAISS-IVF, and HNSW build data dependent indices that offer substantially better accurac…
DECAF: Deep Extreme Classification with Label Features
Anshul Mittal, Kunal Dahiya, Sheshansh Agrawal +4
Extreme multi-label classification (XML) involves tagging a data point with its most relevant subset of labels from an extremely large label set, with several applications such as…
ECLARE: Extreme Classification with Label Graph Correlations
Anshul Mittal, Noveen Sachdeva, Sheshansh Agrawal +3
Deep extreme classification (XC) seeks to train deep architectures that can tag a data point with its most relevant subset of labels from an extremely large label set. The core uti…
Lexicographic Ranking Supermartingales: An Efficient Approach to Termination of Probabilistic Programs
Sheshansh Agrawal, Krishnendu Chatterjee, Petr Novotný
Probabilistic programs extend classical imperative programs with real-valued random variables and random branching. The most basic liveness property for such programs is the termin…