14 citations · 34 across the 16 of their papers we have counts for
8 papers · 1 filter
Distinguishing Ignorance from Error in LLM Hallucinations
Adi Simhi, Jonathan Herzig, Idan Szpektor +1
Large language models (LLMs) are susceptible to hallucinations -- factually incorrect outputs -- leading to a large body of work on detecting and mitigating such cases. We argue th…
DoubleDipper: Improving Long-Context LLMs via Context Recycling
Arie Cattan, Alon Jacovi, Alex Fabrikant +8
Despite recent advancements in Large Language Models (LLMs), their performance on tasks involving long contexts remains sub-optimal. In this work, we propose DoubleDipper, a novel…
TACT: Advancing Complex Aggregative Reasoning with Information Extraction Tools
Avi Caciularu, Alon Jacovi, Eyal Ben-David +5
Large Language Models (LLMs) often do not perform well on queries that require the aggregation of information across texts. To better evaluate this setting and facilitate modeling…
Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?
Zorik Gekhman, Gal Yona, Roee Aharoni +4
When large language models are aligned via supervised fine-tuning, they may encounter new factual information that was not acquired through pre-training. It is often conjectured th…
Constructing Benchmarks and Interventions for Combating Hallucinations in LLMs
Adi Simhi, Jonathan Herzig, Idan Szpektor +1
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 interveni…
Representation Surgery: Theory and Practice of Affine Steering
Shashwat Singh, Shauli Ravfogel, Jonathan Herzig +3
Language models often exhibit undesirable behavior, e.g., generating toxic or gender-biased text. In the case of neural language models, an encoding of the undesirable behavior is…
A Chain-of-Thought Is as Strong as Its Weakest Link: A Benchmark for Verifiers of Reasoning Chains
Alon Jacovi, Yonatan Bitton, Bernd Bohnet +6
Prompting language models to provide step-by-step answers (e.g., "Chain-of-Thought") is the prominent approach for complex reasoning tasks, where more accurate reasoning chains typ…
Multilingual Instruction Tuning With Just a Pinch of Multilinguality
Uri Shaham, Jonathan Herzig, Roee Aharoni +3
As instruction-tuned large language models (LLMs) gain global adoption, their ability to follow instructions in multiple languages becomes increasingly crucial. In this work, we in…