Modality Fault Lines: Structural Corruptions Reveal Fragile Omni-Modal Reasoning

arXiv:2608.29278 · cs.CL · Submitted 2026-08-29 · Read on arXiv

cs.CL

Submitted: 2026-08-29

Updated: 2026-10-04

Comments: EMNLP 2026 Findings

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Accuracy — 84× in this paper · explained in 1 episode
• Benchmark — 42× in this paper · explained in 2 episodes
• Robustness — 35× in this paper · explained in 5 episodes
• Interpretability — 17× in this paper · explained in 15 episodes
• Calibration — 14× in this paper · explained in 7 episodes
• Aggregation — 10× in this paper · explained in 1 episode
• Ablation — 9× in this paper · explained in 1 episode
• Verification — 9× in this paper · explained in 2 episodes
• Benchmarking — 7× in this paper · explained in 4 episodes
• Additivity — 5× in this paper · explained in 1 episode
• Alignment — 5× in this paper · explained in 1 episode
• Core — 5× in this paper · explained in 2 episodes
• Annotator Agreement — 4× in this paper · explained in 1 episode
• Adam — 3× in this paper · explained in 2 episodes
• Distribution Shift — 3× in this paper · explained in 6 episodes
• Hallucination — 3× in this paper · explained in 4 episodes
• Abstention — 2× in this paper · explained in 1 episode
• Consistency — 2× in this paper · explained in 3 episodes
• Failure Modes — 2× in this paper · explained in 3 episodes
• Vision-language models — 2× in this paper · explained in 2 episodes
• Automatic Speech Recognition (ASR) — 1× in this paper · explained in 2 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Knowledge Distillation — 1× in this paper · explained in 11 episodes
• Multimodal Reasoning — 1× in this paper · explained in 5 episodes
• RAG — 1× in this paper · explained in 3 episodes
• Systematic Bias — 1× in this paper · explained in 3 episodes

Sources

• Seeing Across Views: Benchmarking Spatial Reasoning of Vision-Language Models in Robotic Scenes
• How Order-Sensitive Are LLMs? OrderProbe for Deterministic Structural Reconstruction
• Benchmarking Neural Network Robustness to Common Corruptions and Perturbations
• GPT-4o System Card
• QuantEval: A Benchmark for Financial Quantitative Tasks in Large Language Models
• Baichuan-Omni Technical Report
• Ola: Pushing the Frontiers of Omni-Modal Language Model
• Benchmarking Robustness of Multimodal Image-Text Models under Distribution Shift
• SPADER: Step-wise Peer Advantage with Diversity-Aware Exploration Rewards for Multi-Answer Question Answering
• Gemini: A Family of Highly Capable Multimodal Models
• Qwen3.5-Omni Technical Report
• OmniVinci: Enhancing Architecture and Data for Omni-Modal Understanding LLM
• Benchmarking Large Multimodal Models against Common Corruptions

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