Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
41 tokens/sec
GPT-4o
59 tokens/sec
Gemini 2.5 Pro Pro
41 tokens/sec
o3 Pro
7 tokens/sec
GPT-4.1 Pro
50 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Better Retrieval May Not Lead to Better Question Answering (2205.03685v1)

Published 7 May 2022 in cs.CL

Abstract: Considerable progress has been made recently in open-domain question answering (QA) problems, which require Information Retrieval (IR) and Reading Comprehension (RC). A popular approach to improve the system's performance is to improve the quality of the retrieved context from the IR stage. In this work we show that for StrategyQA, a challenging open-domain QA dataset that requires multi-hop reasoning, this common approach is surprisingly ineffective -- improving the quality of the retrieved context hardly improves the system's performance. We further analyze the system's behavior to identify potential reasons.

User Edit Pencil Streamline Icon: https://streamlinehq.com
Authors (5)
  1. Zhengzhong Liang (3 papers)
  2. Tushar Khot (53 papers)
  3. Steven Bethard (16 papers)
  4. Mihai Surdeanu (53 papers)
  5. Ashish Sabharwal (84 papers)
Citations (3)