← Search

Liangliang Liu

2 accepted papers

2026

AgriEval: A Comprehensive Chinese Agricultural Benchmark for Large Language Models

AAAI 2026technical

n the agricultural domain, the deployment of large language models (LLMs) is hindered by the lack of training data and evaluation benchmarks. To mitigate this issue, we propose AgriEval, the first comprehensive Chinese agricultural benchmark with three main characteristics: (1) Comprehensive Capabil

Cited by 0SourcePDFScholar
2026

REAL: Resolving Knowledge Conflicts in Knowledge-Intensive Visual Question Answering via Reasoning-Pivot Alignment

ICML 2026poster

Knowledge-intensive Visual Question Answering (KI-VQA) frequently suffers from severe knowledge conflicts caused by the inherent limitations of open-domain retrieval. However, existing paradigms face critical limitations, including the lack of generalizable conflict detection and intra-model constra…

Cited by 0SourceScholar