Papers with InternVL
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing: Industry Track (2025.emnlp-industry)
Copied to clipboard
| Challenge: | EMNLP 2025 Industry Track highlights key insights, novel research trends and challenges encountered in practical language technology applications. |
| Approach: | Kai Chen will present the technical advances behind the open-source Intern-series large models . he will highlight how models acquire expert-level skills in specialized domains . |
| Outcome: | This talk will highlight the technical advances behind the open-source Intern-series models . it will highlight how models acquire expert-level skills in specialized domains while retaining broad generalization ability. |
\mathsf{Con Instruction}: Universal Jailbreaking of Multimodal Large Language Models via Non-Textual Modalities (2025.acl-long)
Copied to clipboard
| Challenge: | Existing attacks communicate instruction through text, accompanied by a toxic image or audio . a novel gray-box attack method generates adversarial images or audio to convey harmful instructions to MLLMs . |
| Approach: | They propose a gray-box attack method that generates adversarial images or audio to convey specific harmful instructions to MLLMs by following non-textual instruction. |
| Outcome: | The proposed method achieves highest success rates on visual and audio-language models . larger models are more susceptible toCon Instruction, compared to their underlying models - the results will be released . |
TurkingBench: A Challenge Benchmark for Web Agents (2025.naacl-long)
Copied to clipboard
Kevin Xu, Yeganeh Kordi, Tanay Nayak, Adi Asija, Yizhong Wang, Kate Sanders, Adam Byerly, Jingyu Zhang, Benjamin Van Durme, Daniel Khashabi
| Challenge: | TurkingBench is a benchmark consisting of tasks presented as web pages with textual instructions and multi-modal contexts. |
| Approach: | They propose to use HTML pages to perform various annotation tasks on crowdsourcing platforms. |
| Outcome: | The proposed model outperforms other models on the TurkingBench benchmark. |
ClimateViz: A Benchmark for Statistical Reasoning and Fact Verification on Scientific Charts (2025.emnlp-main)
Copied to clipboard
| Challenge: | Scientific fact-checking has largely focused on textual and tabular sources, neglecting scientific charts. |
| Approach: | They propose a benchmark for scientific fact-checking grounded in scientific charts . climateViz comprises 49,862 claims paired with 2,896 visualizations . results show current models struggle to perform fact- checking when statistical reasoning is required . |
| Outcome: | The climateviz benchmark is the first large-scale benchmark for scientific fact-checking . it includes 49,862 claims paired with 2,896 visualizations labeled as support, refute, or not enough . |