activity
20232026
most citedEvaluation of Reinforcement Learning Techniques for Trading on a Diverse Portfolio

2 citations · 3 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CL2026

Next-Concept Modeling: Fast, Parallel Coarse-to-Fine Text Generation

Hermann Kumbong, Ishan S. Khare, Iddah Mlauzi +6

Diffusion language models (DLMs) offer parallel sampling for faster generation than autoregressive models, an increasingly important advantage as inference becomes a dominant compu…

cs.LG2026

Block Parallelism For Efficient Distributed Long-Context Diffusion Language Model Training

Tarun Suresh, Pranshu Chaturvedi, Hangoo Kang +4

Block diffusion language models (BDLMs) combine autoregressive dependencies across blocks with parallel denoising within blocks, but long-context training is constrained by distrib…

cs.LG2025★ 1 cited

An Information Theoretic Perspective on Agentic System Design

Shizhe He, Avanika Narayan, Ishan S. Khare +3

Agentic language model (LM) systems power modern applications like "Deep Research" and "Claude Code," and leverage multi-LM architectures to overcome context limitations. Beneath t…

cs.AI2024

Smoothie: Label Free Language Model Routing

Neel Guha, Mayee F. Chen, Trevor Chow +2

Large language models (LLMs) are increasingly used in applications where LLM inputs may span many different tasks. Recent work has found that the choice of LLM is consequential, an…

cs.AI2024

WONDERBREAD: A Benchmark for Evaluating Multimodal Foundation Models on Business Process Management Tasks

Michael Wornow, Avanika Narayan, Ben Viggiano +15

Existing ML benchmarks lack the depth and diversity of annotations needed for evaluating models on business process management (BPM) tasks. BPM is the practice of documenting, meas…

q-fin.TR2023★ 2 cited

Evaluation of Reinforcement Learning Techniques for Trading on a Diverse Portfolio

Ishan S. Khare, Tarun K. Martheswaran, Akshana Dassanaike-Perera

This work seeks to answer key research questions regarding the viability of reinforcement learning over the S&P 500 index. The on-policy techniques of Value Iteration (VI) and Stat…

stat.AP2023

Actionable Insights on Philadelphia Crime Hot-Spots: Clustering and Statistical Analysis to Inform Future Crime Legislation

Ishan S. Khare, Tarun K. Martheswaran, Rahul K. Thomas +1

Philadelphia's problem with high crime rates continues to be exacerbated as Philadelphia's residents, community leaders, and law enforcement officials struggle to address the root…