Constructing Benchmarks and Interventions for Combating Hallucinations in LLMs Article Swipe
Adi Simhi
,
Jonathan Herzig
,
Idan Szpektor
,
Yonatan Belinkov
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2404.09971
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2404.09971
Large language models (LLMs) are prone to hallucinations, which sparked a widespread effort to detect and prevent them. Recent work attempts to mitigate hallucinations by intervening in the model's generation, typically computing representative vectors of hallucinations vs. grounded generations, for steering the model's hidden states away from a hallucinatory state. However, common studies employ different setups and do not properly separate different possible causes of hallucinations, making interventions misguided. In this work, we introduce a method for categorizing examples based on the model's prior knowledge, named WACK. We construct WACK benchmarks that support interventions in two settings: open-book and closed-book question answering. Using the benchmarks, we perform an extensive investigation of the effect of different choices for intervention, such as the intervened components, and how often and how strongly to intervene. We find that intervention success varies depending on the component, with the attention blocks performing well and the residual stream proving detrimental to language modeling capabilities. We also show that interventions can benefit from representative vectors collected before, rather than after, a hallucination occurs. Finally, we introduce a new dynamic intervention, which intervenes only if needed, and thus is more robust than standard static interventions. The code is available at https://github.com/technion-cs-nlp/hallucination-mitigation .
Related Topics
Concepts
Heuristics
Intervention (counseling)
Psychological intervention
Computer science
Component (thermodynamics)
Code (set theory)
Language model
Block (permutation group theory)
Residual
Psychology
Cognitive psychology
Artificial intelligence
Algorithm
Psychiatry
Mathematics
Thermodynamics
Geometry
Set (abstract data type)
Operating system
Programming language
Physics
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2404.09971
- https://arxiv.org/pdf/2404.09971
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4394868333
All OpenAlex metadata
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https://openalex.org/W4394868333Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2404.09971Digital Object Identifier
- Title
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Constructing Benchmarks and Interventions for Combating Hallucinations in LLMsWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-04-15Full publication date if available
- Authors
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Adi Simhi, Jonathan Herzig, Idan Szpektor, Yonatan BelinkovList of authors in order
- Landing page
-
https://arxiv.org/abs/2404.09971Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2404.09971Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
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https://arxiv.org/pdf/2404.09971Direct OA link when available
- Concepts
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Heuristics, Intervention (counseling), Psychological intervention, Computer science, Component (thermodynamics), Code (set theory), Language model, Block (permutation group theory), Residual, Psychology, Cognitive psychology, Artificial intelligence, Algorithm, Psychiatry, Mathematics, Thermodynamics, Geometry, Set (abstract data type), Operating system, Programming language, PhysicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.effort | 12 |
| abstract_inverted_index.employ | 53 |
| abstract_inverted_index.hidden | 43 |
| abstract_inverted_index.making | 66 |
| abstract_inverted_index.method | 75 |
| abstract_inverted_index.models | 2 |
| abstract_inverted_index.rather | 169 |
| abstract_inverted_index.robust | 191 |
| abstract_inverted_index.setups | 55 |
| abstract_inverted_index.state. | 49 |
| abstract_inverted_index.states | 44 |
| abstract_inverted_index.static | 194 |
| abstract_inverted_index.stream | 150 |
| abstract_inverted_index.varies | 136 |
| abstract_inverted_index.before, | 168 |
| abstract_inverted_index.benefit | 163 |
| abstract_inverted_index.choices | 115 |
| abstract_inverted_index.dynamic | 180 |
| abstract_inverted_index.model's | 28, 42, 82 |
| abstract_inverted_index.needed, | 186 |
| abstract_inverted_index.occurs. | 174 |
| abstract_inverted_index.perform | 106 |
| abstract_inverted_index.prevent | 16 |
| abstract_inverted_index.proving | 151 |
| abstract_inverted_index.sparked | 9 |
| abstract_inverted_index.studies | 52 |
| abstract_inverted_index.success | 135 |
| abstract_inverted_index.support | 92 |
| abstract_inverted_index.vectors | 33, 166 |
| abstract_inverted_index.Finally, | 175 |
| abstract_inverted_index.However, | 50 |
| abstract_inverted_index.attempts | 20 |
| abstract_inverted_index.examples | 78 |
| abstract_inverted_index.grounded | 37 |
| abstract_inverted_index.language | 1, 154 |
| abstract_inverted_index.mitigate | 22 |
| abstract_inverted_index.modeling | 155 |
| abstract_inverted_index.possible | 62 |
| abstract_inverted_index.properly | 59 |
| abstract_inverted_index.question | 100 |
| abstract_inverted_index.residual | 149 |
| abstract_inverted_index.separate | 60 |
| abstract_inverted_index.standard | 193 |
| abstract_inverted_index.steering | 40 |
| abstract_inverted_index.strongly | 128 |
| abstract_inverted_index.attention | 143 |
| abstract_inverted_index.available | 199 |
| abstract_inverted_index.collected | 167 |
| abstract_inverted_index.computing | 31 |
| abstract_inverted_index.construct | 88 |
| abstract_inverted_index.depending | 137 |
| abstract_inverted_index.different | 54, 61, 114 |
| abstract_inverted_index.extensive | 108 |
| abstract_inverted_index.introduce | 73, 177 |
| abstract_inverted_index.open-book | 97 |
| abstract_inverted_index.settings: | 96 |
| abstract_inverted_index.typically | 30 |
| abstract_inverted_index.answering. | 101 |
| abstract_inverted_index.benchmarks | 90 |
| abstract_inverted_index.component, | 140 |
| abstract_inverted_index.intervene. | 130 |
| abstract_inverted_index.intervened | 121 |
| abstract_inverted_index.intervenes | 183 |
| abstract_inverted_index.knowledge, | 84 |
| abstract_inverted_index.misguided. | 68 |
| abstract_inverted_index.performing | 145 |
| abstract_inverted_index.widespread | 11 |
| abstract_inverted_index.benchmarks, | 104 |
| abstract_inverted_index.closed-book | 99 |
| abstract_inverted_index.components, | 122 |
| abstract_inverted_index.detrimental | 152 |
| abstract_inverted_index.generation, | 29 |
| abstract_inverted_index.intervening | 25 |
| abstract_inverted_index.categorizing | 77 |
| abstract_inverted_index.generations, | 38 |
| abstract_inverted_index.intervention | 134 |
| abstract_inverted_index.capabilities. | 156 |
| abstract_inverted_index.hallucination | 173 |
| abstract_inverted_index.hallucinatory | 48 |
| abstract_inverted_index.intervention, | 117, 181 |
| abstract_inverted_index.interventions | 67, 93, 161 |
| abstract_inverted_index.investigation | 109 |
| abstract_inverted_index.hallucinations | 23, 35 |
| abstract_inverted_index.interventions. | 195 |
| abstract_inverted_index.representative | 32, 165 |
| abstract_inverted_index.hallucinations, | 7, 65 |
| abstract_inverted_index.https://github.com/technion-cs-nlp/hallucination-mitigation | 201 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 4 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/16 |
| sustainable_development_goals[0].score | 0.4099999964237213 |
| sustainable_development_goals[0].display_name | Peace, Justice and strong institutions |
| citation_normalized_percentile |