·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
The US spent billions on border surveillance. Why can’t it catch people before they die?1h◆How we made the first comprehensive map of deaths along the US border’s “virtual wall”1h◆4 ways to address the failures we found along the US border’s “virtual wall”1h◆She died at the San Diego border. A surveillance camera was in plain sight1h◆UN says AI safeguards can’t wait for certainty3h◆Amazon doesn’t trust Meta’s Muse AI agent4h◆LoRA Enhanced Contrastive Learning with SAS Vision Transformers9h◆Hallucination-R1: Robustness-Oriented Paraphrase Generation for Factual Consistency9h◆TatBLiMP: A Benchmark of Linguistic Minimal Pairs for Tatar9h◆Runtime Authorization for Resources Acquired by AI Agents9h◆JudgeSense: A Benchmark for Prompt Sensitivity in LLM-as-a-Judge Systems9h◆Multi-Domain Clustering via Measure Quantization9h◆Generative inversion for early ranking of competing geologic interpretations9h◆Do small language models know what they don't know?9h◆Listen Before You Speak: Response Planning from Listener Facial Reactions for Conversational Speech Generation9h◆On Repulsive and Attractive Teachers: Separating Correctness from Behavior in Self-Distillation9h◆Chinese Competitive Debating Dataset and Benchmark9h◆Intent-Governed Tool Authorization for AI Agents9h◆Collaborative Memory for Multi-Agent VLM Systems9h◆The Spoken Wikipedia Presentation Corpus9h◆The US spent billions on border surveillance. Why can’t it catch people before they die?1h◆How we made the first comprehensive map of deaths along the US border’s “virtual wall”1h◆4 ways to address the failures we found along the US border’s “virtual wall”1h◆She died at the San Diego border. A surveillance camera was in plain sight1h◆UN says AI safeguards can’t wait for certainty3h◆Amazon doesn’t trust Meta’s Muse AI agent4h◆LoRA Enhanced Contrastive Learning with SAS Vision Transformers9h◆Hallucination-R1: Robustness-Oriented Paraphrase Generation for Factual Consistency9h◆TatBLiMP: A Benchmark of Linguistic Minimal Pairs for Tatar9h◆Runtime Authorization for Resources Acquired by AI Agents9h◆JudgeSense: A Benchmark for Prompt Sensitivity in LLM-as-a-Judge Systems9h◆Multi-Domain Clustering via Measure Quantization9h◆Generative inversion for early ranking of competing geologic interpretations9h◆Do small language models know what they don't know?9h◆Listen Before You Speak: Response Planning from Listener Facial Reactions for Conversational Speech Generation9h◆On Repulsive and Attractive Teachers: Separating Correctness from Behavior in Self-Distillation9h◆Chinese Competitive Debating Dataset and Benchmark9h◆Intent-Governed Tool Authorization for AI Agents9h◆Collaborative Memory for Multi-Agent VLM Systems9h◆The Spoken Wikipedia Presentation Corpus9h◆
News/AgentVidBench: A Multi-Hop Video Question Answering Benchmark for Evaluating MLLM Agents
arxiv
PublishedSeptember 21, 2026 at 4:00 AM
—neutral

AgentVidBench: A Multi-Hop Video Question Answering Benchmark for Evaluating MLLM Agents

Source
arxiv.orgfull article ↗
Read on arxiv→
Publisher summary· verbatim

arXiv:2609.21386v1 Announce Type: cross Abstract: Comprehensive video understanding is crucial for advancing artificial intelligence toward the intricate dynamics of the physical world. While recent advances in Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities in vid

Stay posted· Newsletter

A 5-min weekly brief — top movers, price watch, story of the week.

// no spam · unsubscribe one-click · free forever

Discussion
Source
↗
arxiv
Read original ↗All from arxiv →

No replies yet. Be first.

Source
↗
arxiv
Read original ↗All from arxiv →

Related coverage

More from ARXIV
arxivLoRA Enhanced Contrastive Learning with SAS Vision Transformers9harxivHallucination-R1: Robustness-Oriented Paraphrase Generation for Factual Consistency9harxivTatBLiMP: A Benchmark of Linguistic Minimal Pairs for Tatar9harxivRuntime Authorization for Resources Acquired by AI Agents9h
The Bubble Brief
WEEKLY

Read AI insights every Tuesday — top movers, new releases, story of the week.

// no spam · unsubscribe one-click · free forever

Originally published on arxiv ↗
HomeModelsNews