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Aman Chadha

ACL 2026×2CVPR 2026ECCV 2026评测与基准多模态检索与知识安全推理
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0 一作 · 4 篇 · ACL 2026 / CVPR 2026 / ECCV 2026

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2026 顶会论文

4
作者位次 #2/4ACL 2026Poster· Natural Language Processing

Can Large Language Models Infer Causal Relationships from Real-World Text?

Ryan Saklad · Aman Chadha · Oleg V. Pavlov · Raha Moraffah

摘要

Understanding and inferring causal relationships from texts is a core aspect of human cognition and is essential for advancing large language models (LLMs) towards artificial general intelligence. Existing work evaluating LLM causal reasoning primarily relies on synthetic or simplified texts with...

评测与基准检索与知识推理OpenReview 项目页
作者位次 #2/5ACL 2026Poster· Natural Language Processing

Paper Circle: An Open-source Multi-agent Research Discovery and Analysis Framework

Komal Kumar · Aman Chadha · Salman Khan · Fahad Shahbaz Khan · Hisham Cholakkal

摘要

The rapid growth of scientific literature has made it increasingly difficult for researchers to efficiently discover, evaluate, and synthesize relevant work. Recent advances in multi-agent large language models (LLMs) have demonstrated strong potential for understanding user intent and are being...

检索与知识智能体与工具评测与基准OpenReview 项目页

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