hypothesis

active

hypothesis:we-hypothesize-that-hallucinated-rationales-in-1b-models-result-from-lack-of-necessary-vision-context-incorporating-vision-features-should-reduce-hallucination-and-improve-rationale-quality

We hypothesize that hallucinated rationales in 1B-models result from lack of necessary vision context; incorporating vision features should reduce hallucination and improve rationale quality.

Predictive hypothesis driving the investigation in Section 3.3; supported by experimental evidence.

Source paper

extracted_from

Multimodal Chain-of-Thought Reasoning in Language Models

(2023) · Zhuosheng Zhang · Aston Zhang · Mu Li · Hai Zhao +2

Neighborhood — ranked by edge-count

Findings (1)

finding

60.7% of hallucination mistakes corrected by adding vision features in two-stage framework on ScienceQA
answered_by
Quantitative evidence that vision information mitigates hallucinated rationales; 56% of error cases contained hallucinations, 60.7% of which were resolved with vision features.

Related by similarity (8)

cosine ≥ 0.65 · no typed edge

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