Papers with information dissemination
The Hidden Bias: A Study on Explicit and Implicit Political Stereotypes in Large Language Models (2026.findings-eacl)
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| Challenge: | Large Language Models (LLMs) are increasingly integral to information dissemination and decision-making processes. |
| Approach: | They investigate political bias and stereotype propagation across eight prominent LLMs using the two-dimensional Political Compass Test. |
| Outcome: | The political bias and stereotype propagation of large language models is investigated using the two-dimensional Political Compass Test (PCT) key findings reveal a left-leaning political alignment across all investigated models. |
RedOne: Revealing Domain-specific LLM Post-Training in Social Networking Services (2025.emnlp-industry)
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Fei Zhao, Chonggang Lu, null Wangyue, Zheyong Xie, Ziyan Liu, Haofu Qian, Jianzhao Huang, Fangcheng Shi, Zijie Meng, Hongcheng Guo, Mingqian He, Xinze Lyu, Zheyu Ye, Weiting Liu, Boyang Wang, Shaosheng Cao
| Challenge: | Social networking services (SNS) have experienced rapid growth, which has proposed significant challenges for platform content management and interaction quality improvement. |
| Approach: | They propose a domain-specific LLM to break the performance bottleneck of single-task baselines and establish a comprehensive foundation for social networking services. |
| Outcome: | The proposed model achieves an average improvement of 14.02% across 8 major tasks and 7.56% in bilingual evaluation benchmark, compared with baseline models. |
Global Readiness of Language Technology for Healthcare: What Would It Take to Combat the Next Pandemic? (2022.coling-1)
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| Challenge: | Language Technology (LT) has been used in the COVID-19 pandemic, but only in a handful of languages. |
| Approach: | They propose to use conversational agents for information dissemination and basic diagnosis in 15 Asian and African languages with varying resource-availability to test their knowledge of LT. |
| Outcome: | The proposed research confirms the pitiful state of LT even for languages with large speaker bases, such as Sinhala and Hausa, and identifies the gaps that could help prioritize research and investment strategies in LT for healthcare. |
Empowering the Fact-checkers! Automatic Identification of Claim Spans on Twitter (2022.emnlp-main)
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| Challenge: | Current vogue is to employ manual fact-checkers to efficiently classify and verify such data to combat this avalanche of misinformation and fake news. |
| Approach: | They propose a large-scale Twitter corpus with token-level claim spans on more than 7.5k tweets and a model that automatically detects and extracts the snippets of misinformation. |
| Outcome: | The proposed model outperforms baseline systems on several evaluation metrics, improving by 1.5 points. |
FactVerse: A Benchmark for Factual Consistency in Interleaved Image–Text Generation (2026.acl-long)
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Yubo Shan, Kun Zhang, Qiming Xu, Liping Cao, Yingying Cao, Jian Zhang, Yu Wang, Jingyuan Li, Yuanzhuo Wang
| Challenge: | Existing benchmarks lack effective mechanisms to evaluate factual consistency in interleaved image-text generation. |
| Approach: | They propose a benchmark dedicated to evaluating factual consistency in interleaved image-text generation. |
| Outcome: | The proposed framework outperforms existing evaluation methods in evaluating factual consistency in interleaved image-text generation. |