1 citations · 1 across the 6 of their papers we have counts for
6 papers
Compression-Aware Abstention: Teaching LLMs to Refuse When KV-Compression Masks Remove Answer Evidence
Mohammadali Khodabandehlou, Bhaskar Krishnamachari
KV-cache compression reduces LLM inference memory by evicting context tokens, but when the evicted tokens contain answer-bearing evidence, the model may hallucinate instead of reco…
TS-Verkle: A TypeScript Native Verkle Library With On-chain Verifier
Zhikai Li, Xuekai Liu, Boyuan Xu +2
Blockchain systems face significant scalability challenges due to growing data volumes and increasing transaction demands, necessitating more efficient data structures and verifica…
Do Prediction Markets Forecast Cryptocurrency Volatility? Evidence from Kalshi Macro Contracts
Hardhik Mohanty, Bhaskar Krishnamachari
Daily probability changes in Kalshi macro prediction markets forecast cryptocurrency realized volatility through two distinct channels. The monetary policy channel, measured by Fed…
Cluster-based Adaptive Retrieval: Dynamic Context Selection for RAG Applications
Yifan Xu, Vipul Gupta, Rohit Aggarwal +2
Retrieval-Augmented Generation (RAG) enhances large language models (LLMs) by pulling in external material, document, code, manuals, from vast and ever-growing corpora, to effectiv…
RiskSEA : A Scalable Graph Embedding for Detecting On-chain Fraudulent Activities on the Ethereum Blockchain
Ayush Agarwal, Lv Lu, Arjun Maheswaran +2
Like any other useful technology, cryptocurrencies are sometimes used for criminal activities. While transactions are recorded on the blockchain, there exists a need for a more rap…
ML2SC: Deploying Machine Learning Models as Smart Contracts on the Blockchain
Zhikai Li, Steve Vott, Bhaskar Krishnamachar
With the growing concern of AI safety, there is a need to trust the computations done by machine learning (ML) models. Blockchain technology, known for recording data and running c…