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MTBench: A Multimodal Time Series Benchmark for Temporal Reasoning and Question Answering
arXiv.orgUnderstanding the relationship between textual news and time-series evolution is a critical yet under-explored challenge in applied data science. While multimodal learning has gained traction, existing multimodal time-series datasets fall short in ...
Jia-Lin Chen +9 more
semanticscholar +1 more source
ChronoEdit: Towards Temporal Reasoning for Image Editing and World Simulation
arXiv.orgRecent advances in large generative models have greatly enhanced both image editing and in-context image generation, yet a critical gap remains in ensuring physical consistency, where edited objects must remain coherent.
J. Wu +13 more
semanticscholar +1 more source
Temporal Reasoning with Aspectual Adverbs
Linguistics and Philosophy, 2002Our central aim is to account for the validity of reasoning patterns involving focus adverbs in contexts where the temporal reference point may change during the process of interpretation of the premises. This paper proposes a dynamic semantics of such temporal inferences, determining what is updated in the interpretation and what information is ...
Alice ter Meulen, Hans Smessaert
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TIME: A Multi-level Benchmark for Temporal Reasoning of LLMs in Real-World Scenarios
Neural Information Processing SystemsTemporal reasoning is pivotal for Large Language Models (LLMs) to comprehend the real world. However, existing works neglect the real-world challenges for temporal reasoning: (1) intensive temporal information, (2) fast-changing event dynamics, and (3 ...
Shaohang Wei +7 more
semanticscholar +1 more source
Temporal Reasoning in Medicine
2005This chapter aims to give a comprehensive and critical review of current approaches to temporal reasoning in medical applications, and to suggest future research directions. The chapter begins by presenting the relevant time representation and temporal reasoning requirements.
Shahar, Yuval +1 more
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Time-R1: Towards Comprehensive Temporal Reasoning in LLMs
arXiv.orgLarge Language Models (LLMs) demonstrate impressive capabilities but lack robust temporal intelligence, struggling to integrate reasoning about the past with predictions and plausible generations of the future.
Zi-Jia Liu +4 more
semanticscholar +1 more source
Learn from Relational Correlations and Periodic Events for Temporal Knowledge Graph Reasoning
Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023Reasoning on temporal knowledge graphs (TKGR), aiming to infer missing events along the timeline, has been widely studied to alleviate incompleteness issues in TKG, which is composed of a series of KG snapshots at different timestamps.
K. Liang +7 more
semanticscholar +1 more source
Daily-Omni: Towards Audio-Visual Reasoning with Temporal Alignment across Modalities
arXiv.orgRecent Multimodal Large Language Models (MLLMs) achieve promising performance on visual and audio benchmarks independently. However, the ability of these models to process cross-modal information synchronously remains largely unexplored.
Ziwei Zhou, Rui Wang, Zuxuan Wu
semanticscholar +1 more source
Annual Meeting of the Association for Computational Linguistics
Temporal reasoning in multi-session dialogues presents a significant challenge which has been under-studied in previous temporal reasoning benchmarks. To bridge this gap, we propose a new evaluation task for temporal reasoning in multi-session dialogues ...
Yubin Ge +6 more
semanticscholar +1 more source
Temporal reasoning in multi-session dialogues presents a significant challenge which has been under-studied in previous temporal reasoning benchmarks. To bridge this gap, we propose a new evaluation task for temporal reasoning in multi-session dialogues ...
Yubin Ge +6 more
semanticscholar +1 more source
The Devil is in Temporal Token: High Quality Video Reasoning Segmentation
Computer Vision and Pattern RecognitionExisting methods for Video Reasoning Segmentation rely heavily on a single special token to represent the object in the keyframe or the entire video, inadequately capturing spatial complexity and inter-frame motion.
Sitong Gong +5 more
semanticscholar +1 more source