activity
20242026
collaborators

8 papers

cs.AI2026

Not Worth Another Token: Marginal Value Estimation for Efficient Deep Research Agents

Harshitha Kolukuluru, Reshma Ashok, Kirat Arora +7

Long-horizon research agents solve open-ended tasks through iterative retrieval, aggregation, and synthesis, but context grows rapidly while the marginal value of additional eviden…

cs.DC2025

Efficient Tree-Structured Deep Research with Adaptive Resource Allocation

Lunyiu Nie, Nedim Lipka, Ryan A. Rossi +1

Deep research agents, which synthesize information across diverse sources, are significantly constrained by the sequential nature of reasoning. This bottleneck results in high late…

cs.CL2025

Exploring Rewriting Approaches for Different Conversational Tasks

Md Mehrab Tanjim, Ryan A. Rossi, Mike Rimer +9

Conversational assistants often require a question rewriting algorithm that leverages a subset of past interactions to provide a more meaningful (accurate) answer to the user's que…

cs.CL2025

Towards Optimal Multi-draft Speculative Decoding

Zhengmian Hu, Tong Zheng, Vignesh Viswanathan +5

Large Language Models (LLMs) have become an indispensable part of natural language processing tasks. However, autoregressive sampling has become an efficiency bottleneck. Multi-Dra…

cs.CV2024

Personalized Multimodal Large Language Models: A Survey

Junda Wu, Hanjia Lyu, Yu Xia +24

Multimodal Large Language Models (MLLMs) have become increasingly important due to their state-of-the-art performance and ability to integrate multiple data modalities, such as tex…

cs.AI2024

ScaleViz: Scaling Visualization Recommendation Models on Large Data

Ghazi Shazan Ahmad, Shubham Agarwal, Subrata Mitra +4

Automated visualization recommendations (vis-rec) help users to derive crucial insights from new datasets. Typically, such automated vis-rec models first calculate a large number o…

cs.CL2024

A Framework for Fine-Tuning LLMs using Heterogeneous Feedback

Ryan Aponte, Ryan A. Rossi, Shunan Guo +5

Large language models (LLMs) have been applied to a wide range of tasks, including text summarization, web navigation, and chatbots. They have benefitted from supervised fine-tunin…

cs.CL2024

KaPQA: Knowledge-Augmented Product Question-Answering

Swetha Eppalapally, Daksh Dangi, Chaithra Bhat +8

Question-answering for domain-specific applications has recently attracted much interest due to the latest advancements in large language models (LLMs). However, accurately assessi…