WikiPossessions: Possession Timeline Generation as an Evaluation Benchmark for Machine Reading Comprehension of Long Texts (2020.lrec-1)
Copied to clipboard
| Challenge: | a new corpus of articles is created for the task of temporally-oriented possession . the task is open-domain and can be used to track possession in other texts . |
| Approach: | They propose a new corpus for the task of temporally-oriented possession . they annotate Wikipedia articles for 90 different well-known artifacts . |
| Outcome: | The proposed task is based on annotated Wikipedia articles for 90 artifacts, including paintings, diamonds, and archaeological artifos. |
Similar Papers
Possessors Change Over Time: A Case Study with Artworks (D18-1)
Copied to clipboard
| Challenge: | Existing methods to extract possession relations from Wikipedia articles can be used to extract possessors over time. |
| Approach: | They propose to extract possession relations from Wikipedia articles and temporal information indicating when these relations are true. |
| Outcome: | The proposed annotation scheme yields many possessors over time for a given artwork, and an LSTM ensemble can automate the task. |
Mining Possessions: Existence, Type and Temporal Anchors (N18-1)
Copied to clipboard
| Challenge: | Existing annotations for possession relations can be used to predict possession existence, possession type and temporal anchors. |
| Approach: | They propose to use text annotations to mine possession relations from text . they assign temporal anchors indicating when possession holds between possessor and possessee . |
| Outcome: | The proposed task can predict possession existence, possession type and temporal anchors, and it can be automated. |
TemporalWiki: A Lifelong Benchmark for Training and Evaluating Ever-Evolving Language Models (2022.emnlp-main)
Copied to clipboard
Joel Jang, Seonghyeon Ye, Changho Lee, Sohee Yang, Joongbo Shin, Janghoon Han, Gyeonghun Kim, Minjoon Seo
| Challenge: | Language Models (LMs) become outdated as the world changes, a phenomenon called temporal misalignment. |
| Approach: | They propose a lifelong benchmark that utilizes the difference between consecutive snapshots of English Wikipedia and English Wikidata for training and evaluation. |
| Outcome: | The proposed benchmark can be trained on the difference between consecutive snapshots of English Wikipedia and English Wikidata for training and evaluation. |
Annotating Temporal Dependency Graphs via Crowdsourcing (2020.emnlp-main)
Copied to clipboard
| Challenge: | Existing temporal annotation schemes have been limited due to the complexity of temporal relations between events. |
| Approach: | They propose to build a corpus of Wikinews articles annotated with temporal dependency graphs . they also propose a crowdsourcing strategy to annotate TDGs based on the corpus . |
| Outcome: | The proposed method achieves a good trade-off between completeness and practicality in temporal annotation. |
CaTS-Bench: Can Language Models Describe Time Series? (2026.findings-acl)
Copied to clipboard
| Challenge: | Existing time series captioning benchmarks rely on fully synthetic or generic captions . authors propose a pipeline for generating high-fidelity synthetic captions, which is validated . |
| Approach: | They propose a benchmark for Context-aware Time Series reasoning across 11 diverse domains . they evaluate leading Vision-Language Models on their benchmark . |
| Outcome: | The proposed benchmark evaluates 1746 human-rewritten captions and shows they perform better than open-source models. |
KnowMe-Bench: Benchmarking Person Understanding for Lifelong Digital Companions (2026.acl-long)
Copied to clipboard
Tingyu Wu, Zhisheng Chen, Ziyan Weng, Shuhe Wang, Shuo Zhang, Sen Hu, Silin Wu, Qizhen Lan, Huacan Wang, Ronghao Chen
| Challenge: | Existing long-horizon memory benchmarks use multi-turn dialogues or synthetic user histories . despite rapid progress on long-term memory evaluation, there are gaps in existing benchmarks . |
| Approach: | They propose a long-form autobiographical narrative benchmark that reconstructs each narrative into a flashback-aware, time-anchored stream and evaluates models with evidence-linked questions. |
| Outcome: | The proposed benchmarks build from long-form autobiographical narratives . they show that retrieval-augmented systems improve factual accuracy while errors persist on temporally grounded explanations and higher-level inferences. |
TORQUE: A Reading Comprehension Dataset of Temporal Ordering Questions (2020.emnlp-main)
Copied to clipboard
| Challenge: | Current machine reading comprehension benchmarks have no questions that test temporal phenomena . a new study studies reading comprehension for temporal relations . |
| Approach: | They propose a reading comprehension benchmark built on news snippets and 21k human-generated questions querying temporal relationships. |
| Outcome: | The new reading comprehension benchmark TORQUE achieves an exact-match score of 51% on the test set . the benchmark is built on 3.2k news snippets with 21k human-generated questions . |
Time-dependent Entity Embedding is not All You Need: A Re-evaluation of Temporal Knowledge Graph Completion Models under a Unified Framework (2021.emnlp-main)
Copied to clipboard
| Challenge: | Various temporal knowledge graph (KG) completion models have been proposed . knowledge graphs are typically static and store facts in their current state . |
| Approach: | They propose to use temporal embeddings and a score function to model temporal knowledge graphs . they classify the temporal embedded methods into two classes: timestamp and time-dependent . |
| Outcome: | The proposed models outperform current models on ICEWS datasets with 3000 experiments and 13159 GPU hours. |
Fine-Grained Temporal Relation Extraction (P19-1)
Copied to clipboard
| Challenge: | Existing methods for temporal relations and event durations are insufficient for determining the fine-grained temporal structure of complex events. |
| Approach: | They propose a semantic framework for temporal relations and event durations that maps pairs of events to real-valued scales. |
| Outcome: | The proposed framework can predict fine-grained temporal relations and event durations . it can be applied to the entire English Web Treebank dataset . |
ChronoSense: Exploring Temporal Understanding in Large Language Models with Time Intervals of Events (2025.acl-short)
Copied to clipboard
| Challenge: | Large Language Models (LLMs) still face significant challenges in reasoning and arithmetic. |
| Approach: | They propose a new benchmark to evaluate LLMs' temporal understanding that includes 16 tasks identifying the Allen relation between two temporal events and temporal arithmetic. |
| Outcome: | The proposed model handles Allen relations, even symmetrical ones, quite differently. |