14 citations · 32 across the 32 of their papers we have counts for
6 papers · 1 filter
EigenLI: Spectral Approximations to Late Interaction
Archish S, Sabyasachi Basu, Ankit Garg +2
Late-interaction models such as ColBERT achieve strong effectiveness by representing each document with many token-level vectors, but this expressivity leads to large indexing cost…
Retrieval Needs Multivectors: An Exponential Separation
Mihir Agarwal, Viraj Agrawal, Sabyasachi Basu +2
Recent works have highlighted the expressive limitations of embedding based retrieval models through both theoretical analyses and challenging benchmarks such as LIMIT. While multi…
Quantization Beyond Uniform Bit Allocation
K. S. Sreeramji, Sabyasachi Basu, Ravishankar Krishnaswamy +2
Quantization is a fundamental technique to handle the growing sizes of embeddings generated by modern models. Existing quantization schemes are largely embedding agnostic and alloc…
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…
Chow-Liu Ordering for Long-Context Reasoning in Chain-of-Agents
Naman Gupta, Vaibhav Singh, Arun Iyer +8
Sequential multi-agent reasoning frameworks such as Chain-of-Agents (CoA) handle long-context queries by decomposing inputs into chunks and processing them sequentially using LLM-b…
Welfarist Formulations for Diverse Similarity Search
Siddharth Barman, Nirjhar Das, Shivam Gupta +1
Nearest Neighbor Search (NNS) is a fundamental problem in data structures with wide-ranging applications, such as web search, recommendation systems, and, more recently, retrieval-…