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Vasily Konovalov

SIGIR 2026×2ACL 2026NeurIPS 2026评测与基准多模态检索与知识对齐与偏好效率与系统
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0 一作 · 4 篇 · SIGIR 2026 / ACL 2026 / NeurIPS 2026

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2026 顶会论文

4
作者位次 #2/2NeurIPS 2026Poster

AI-Generated Content Should Be Evaluated by Its Substance, Not Its Source

Anastasia Voznyuk · Vasily Konovalov

评测与基准OpenReview
作者位次 #6/8ACL 2026Workshop· Natural Language Processing

Fine-Grained Semantic Comparison of Legal Documents using LLM s

Elisei Rykov · Nikolay Ivanov · Maria Bandulevich · Kseniia Petrushina · Valentin Malykh · Vasily Konovalov · Alexander Panchenko · Ilseyar Alimova

摘要

Frequent revisions of complex regulatory documents in large organizations often introduce inconsistencies and contradictions that are difficult for lawyers and auditors to detect manually. Existing tools rely on character-level diffs and therefore miss paraphrases and semantic shifts. We introduc...

多模态评测与基准对齐与偏好OpenReview 项目页
作者位次 #6/8SIGIR 2026Poster· Information Retrieval (Demo)

SLeDoC: System for Legal Document Comparison

Elisei Rykov · Nikolay Ivanov · Kseniia Petrushina · Maria Bandulevich · Valentin Malykh · Vasily Konovalov · Alexander Panchenko · Ilseyar Alimova

摘要

Frequent revisions of complex, lengthy regulatory documents in large organizations often create inconsistencies and contradictions that lawyers and auditors find difficult to detect manually. Existing tools rely on character-level diffs that fail to capture paraphrases and semantic shifts. We pre...

多模态评测与基准检索与知识OpenReview
作者位次 #4/7SIGIR 2026Poster· Information Retrieval (Demo)

FactOWL: A Cost-Efficient Tool for Long-Form Factuality Evaluation

Andrey Sakhovskiy · Nikita Sushko · Maria Marina · Vasily Konovalov · Elena Tutubalina · Alexander Panchenko · Pavel Braslavski

摘要

The presence of factual hallucinations in large language model (LLM) generations drives the development of retrieval-augmented factuality evaluation tools. However, existing implementations suffer from slow inference, outdated knowledge bases, and the use of paid search and LLM APIs, which hinder...

检索与知识效率与系统安全OpenReview

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