Papers with TAC
Router-Suggest: Dynamic Routing for Multimodal Auto-Completion in Visually-Grounded Dialogs (2026.eacl-industry)
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| Challenge: | a task that grounds predictions in multimodal context is essential for chatbots, chatbot systems and healthcare consultations. |
| Approach: | They propose a task that grounds predictions in multimodal context to better capture user intent. |
| Outcome: | The proposed task can be used to predict upcoming characters in live chats using partially typed text and visual cues. |
When ACE met KBP: End-to-End Evaluation of Knowledge Base Population with Component-level Annotation (L18-1)
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| Challenge: | Automating constructing a Knowledge Base from unstructured text is a goal of natural language processing. |
| Approach: | They propose a method to evaluate a Knowledge Base population from unstructured text . they propose bootstrap resampling to provide statistical significance to the results . |
| Outcome: | The proposed method uses component-level annotations to evaluate Cold Start KBP . it also uses bootstrap resampling to provide statistical significance to the results reported . |
Neural Cross-Lingual Coreference Resolution And Its Application To Entity Linking (P18-2)
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| Challenge: | a cross-lingual coreference model is based on multi-lingual embeddings and language independent features. |
| Approach: | They propose a crosslingual coreference model that builds on multi-lingual embeddings and language independent features. |
| Outcome: | The proposed model outperforms the existing models on Chinese and Spanish test sets. |
Laying the Groundwork for Knowledge Base Population: Nine Years of Linguistic Resources for TAC KBP (L18-1)
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| Challenge: | Knowledge Base Population (KBP) evaluations target information extraction technologies for knowledge bases comprised of entities, relations, and events. |
| Approach: | They describe the linguistic resources provided by Linguistic Data Consortium for TAC KBP since 2009 . they highlight changes made to support evolving evaluation requirements . |
| Outcome: | The evaluations have targeted information extraction technologies for the population of knowledge bases comprised of entities, relations, and events. |
Towards Sentiment and Emotion aided Multi-modal Speech Act Classification in Twitter (2021.naacl-main)
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| Challenge: | Speech Act Classification determining the communicative intent of an utterance has been investigated widely over the years as a standalone task. |
| Approach: | They propose a multi-modal, emotion-TA dataset called EmoTA from open-source Twitter dataset and a Dyadic Attention Mechanism framework that integrates intra-modal and inter-modal attention to fuse multiple modalities. |
| Outcome: | The proposed framework boosts the performance of the primary task, i.e., TA classification (TAC), by benefitting from the two secondary tasks, namely, Sentiment and Emotion Analysis compared to its uni-modal and single task TAC variants. |
D-Artemis: A Deliberative Cognitive Framework for Mobile GUI Multi-Agents (2026.findings-acl)
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Hongze Mi, Yibo Feng, WenJie Lu, Yuqi Wang, Jinyuan Li, Song Cao, He Cui, Tengfei Tian, Xuelin Zhang, Haotian Luo, Di Sun, Jun Fang, Hua Chai, Naiqiang Tan, Gang Pan
| Challenge: | Graphical User Interface (GUI) agents aim to automate a wide spectrum of human tasks by emulating user interaction. |
| Approach: | They propose a deliberative framework that leverages a fine-grained tip retrieval mechanism to inform its decision-making process. |
| Outcome: | The proposed framework achieves SOTA among open-source general models on AndroidWorld and ScreenSpot-V2 . it leverages a fine-grained, app-specific tip retrieval mechanism to inform its decision-making process . |
Libra: Leveraging Temporal Images for Biomedical Radiology Analysis (2025.findings-acl)
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| Challenge: | Existing methods for radiology report generation rely on single-image analysis or rule-based heuristics to process multiple images. |
| Approach: | They propose a temporal-aware MLLM tailored for chest X-ray report generation that combines a radiology-specific image encoder with a novel Temporal Alignment Connector. |
| Outcome: | The proposed model sets new standards in clinical relevance and lexical accuracy on the MIMIC-CXR dataset. |
Towards Self-Evolving Agents: Enabling Autonomy through Interactive Experience Refinement (2026.findings-acl)
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Cheng Yang, Xuemeng Yang, Licheng Wen, Daocheng Fu, Jianbiao Mei, Rong Wu, Pinlong Cai, Yufan Shen, Nianchen Deng, Jia Xu, Botian Shi, Yu Qiao, Haifeng Li
| Challenge: | Large Language Models struggle with complex, multi-step operational tasks because they remain static during inference and cannot learn from past experience. |
| Approach: | They propose a framework that organizes cross-domain insights to facilitate orchestration of long-horizon workflows. |
| Outcome: | The proposed framework outperforms existing methods on the TAC productivity benchmark and shows strong cross-task transferability. |