9 citations · 9 across the 1 of their papers we have counts for
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ToolDreamer: Instilling LLM Reasoning Into Tool Retrievers
Saptarshi Sengupta, Zhengyu Zhou, Jun Araki +4
Tool calling has become increasingly popular for Large Language Models (LLMs). However, for large tool sets, the resulting tokens would exceed the LLM's context window limit, makin…
DelucionQA: Detecting Hallucinations in Domain-specific Question Answering
Mobashir Sadat, Zhengyu Zhou, Lukas Lange +6
Hallucination is a well-known phenomenon in text generated by large language models (LLMs). The existence of hallucinatory responses is found in almost all application scenarios e.…
Learning to Filter Context for Retrieval-Augmented Generation
Zhiruo Wang, Jun Araki, Zhengbao Jiang +2
On-the-fly retrieval of relevant knowledge has proven an essential element of reliable systems for tasks such as open-domain question answering and fact verification. However, beca…