4 citations · 7 across the 10 of their papers we have counts for
5 papers · 1 filter
FutureWeaver: Planning Test-Time Compute for Multi-Agent Systems with Modularized Collaboration
Dongwon Jung, Peng Shi, Muhao Chen +1
Scaling test-time computation has been shown to significantly improve large language model (LLM) performance without additional training. However, extending these techniques to mul…
IPR: Intelligent Prompt Routing with User-Controlled Quality-Cost Trade-offs
Aosong Feng, Balasubramaniam Srinivasan, Yun Zhou +14
Routing incoming queries to the most cost-effective LLM while maintaining response quality poses a fundamental challenge in optimizing performance-cost trade-offs for large-scale c…
Log-Augmented Generation: Scaling Test-Time Reasoning with Reusable Computation
Peter Baile Chen, Yi Zhang, Dan Roth +3
While humans naturally learn and adapt from past experiences, large language models (LLMs) and their agentic counterparts struggle to retain reasoning from previous tasks and apply…
On Synthetic Data Strategies for Domain-Specific Generative Retrieval
Haoyang Wen, Jiang Guo, Yi Zhang +2
This paper investigates synthetic data generation strategies in developing generative retrieval models for domain-specific corpora, thereby addressing the scalability challenges in…
Can we Retrieve Everything All at Once? ARM: An Alignment-Oriented LLM-based Retrieval Method
Peter Baile Chen, Yi Zhang, Michael Cafarella +1
Real-world open-domain questions can be complicated, particularly when answering them involves information from multiple information sources. LLMs have demonstrated impressive perf…