Papers by Avshalom Manevich
Draw Me a Flower: Processing and Grounding Abstraction in Natural Language (2022.tacl-1)
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| Challenge: | Abstraction is a core tenet of human cognition and communication. yet, interpreting and grounding abstraction expressed in natural language (NL) has not been systematically studied in NLP. |
| Approach: | They propose a 2D instruction-following game that elicits abstract instructions from 4k natural language instructions. |
| Outcome: | The proposed method elicits 4k natural language instructions rich with diverse types of abstractions and assesses neural models. |
Multi Document Summarization Evaluation in the Presence of Damaging Content (2023.findings-emnlp)
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| Challenge: | Existing metrics evaluate a summary based on relevance and consistency with the source documents. |
| Approach: | They propose to measure the ability of MDS systems to handle damaging documents in their input set by lexical similarity and language model likelihood. |
| Outcome: | The proposed metrics show that they can summarize a set of documents without damaging content. |
Mitigating Hallucinations in Large Vision-Language Models (LVLMs) via Language-Contrastive Decoding (LCD) (2024.findings-acl)
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| Challenge: | Large Vision-Language Models (LVLMs) often produce object hallucinations due to their reliance on text cues and learned object co-occurrence biases. |
| Approach: | They propose a language-contrasting decoding algorithm that adjusts LVLM outputs based on LLM confidence levels to mitigate object hallucinations. |
| Outcome: | The proposed method shows up to %4 improvement in POPE F1 scores and %36 reduction in CHAIR scores on COCO validation set while improving captioning quality scores. |