YoCausal benchmark shows video diffusion models detect the arrow of time but lack genuine causal understanding relative to humans.
Version 5, last revised 17 Apr 2025
4 Pith papers cite this work, alongside 1 external citations. Polarity classification is still indexing.
4
Pith papers citing it
1
external citations · external index
citation-role summary
background 1
citation-polarity summary
years
2026 4verdicts
UNVERDICTED 4roles
background 1polarities
background 1representative citing papers
CauSim turns scarce causal reasoning labels into scalable supervised data by having LLMs incrementally construct complex executable structural causal models.
RSICCLLM introduces a post-training framework with RSICI dataset, difference-aware supervised fine-tuning, and dual-negative preference optimization that claims to outperform much larger models on remote sensing image change captioning.
OracleAnalyser applies post-training and a new Stable Focal Preference Optimization algorithm to a 3B MLLM for oracle bone script analysis, releasing datasets and a benchmark where the small model outperforms larger ones.
citing papers explorer
-
YoCausal: How Far is Video Generation from World Model? A Causality Perspective
YoCausal benchmark shows video diffusion models detect the arrow of time but lack genuine causal understanding relative to humans.
-
CauSim: Scaling Causal Reasoning with Increasingly Complex Causal Simulators
CauSim turns scarce causal reasoning labels into scalable supervised data by having LLMs incrementally construct complex executable structural causal models.
-
RSICCLLM: A Multimodal Large Language Model for Remote Sensing Image Change Captioning
RSICCLLM introduces a post-training framework with RSICI dataset, difference-aware supervised fine-tuning, and dual-negative preference optimization that claims to outperform much larger models on remote sensing image change captioning.
-
OracleAnalyser: Analysing Implicit Semantics of Oracle Bone Scripts through MLLMs with Post-training
OracleAnalyser applies post-training and a new Stable Focal Preference Optimization algorithm to a 3B MLLM for oracle bone script analysis, releasing datasets and a benchmark where the small model outperforms larger ones.