3 papers
cs.IR2026
On Strengths and Limitations of Single-Vector Embeddings
Archish S, Mihir Agarwal, Ankit Garg +2
Recent work (Weller et al., 2025) introduced a naturalistic dataset called LIMIT and showed empirically that a wide range of popular single-vector embedding models suffer substanti…
cs.IR2025
Incorporating Token Importance in Multi-Vector Retrieval
Archish S, Ankit Garg, Kirankumar Shiragur +1
ColBERT introduced a late interaction mechanism that independently encodes queries and documents using BERT, and computes similarity via fine-grained interactions over token-level…
cs.PL2025
Equivalence Checking of ML GPU Kernels
Kshitij Dubey, Benjamin Driscoll, Anjiang Wei +3
With the rapid progress of deep learning and large language models (LLMs), companies spend enormous sums executing GPU kernels. These kernels have become prime targets for aggressi…