4 citations · 7 across the 10 of their papers we have counts for
10 papers
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…
Open Domain Question Answering with Conflicting Contexts
Siyi Liu, Qiang Ning, Kishaloy Halder +8
Open domain question answering systems frequently rely on information retrieved from large collections of text (such as the Web) to answer questions. However, such collections of t…
BEAVER: An Enterprise Benchmark for Text-to-SQL
Peter Baile Chen, Devin Yang, Weiyue Li +6
Existing text-to-SQL benchmarks have largely been constructed from public databases with well-structured schemas and simplistic question-SQL pairs. While large language models (LLM…
MDCR: A Dataset for Multi-Document Conditional Reasoning
Peter Baile Chen, Yi Zhang, Chunwei Liu +3
The same real-life questions posed to different individuals may lead to different answers based on their unique situations. For instance, whether a student is eligible for a schola…
Is Table Retrieval a Solved Problem? Exploring Join-Aware Multi-Table Retrieval
Peter Baile Chen, Yi Zhang, Dan Roth
Retrieving relevant tables containing the necessary information to accurately answer a given question over tables is critical to open-domain question-answering (QA) systems. Previo…
ScienceBenchmark: A Complex Real-World Benchmark for Evaluating Natural Language to SQL Systems
Yi Zhang, Jan Deriu, George Katsogiannis-Meimarakis +3
Natural Language to SQL systems (NL-to-SQL) have recently shown a significant increase in accuracy for natural language to SQL query translation. This improvement is due to the eme…