Summary of Paired Completion: Flexible Quantification Of Issue-framing at Scale with Llms, by Simon D Angus and Lachlan O’neill
Paired Completion: Flexible Quantification of Issue-framing at Scale with LLMsby Simon D Angus, Lachlan O'NeillFirst…
Paired Completion: Flexible Quantification of Issue-framing at Scale with LLMsby Simon D Angus, Lachlan O'NeillFirst…
Characterizing and Evaluating the Reliability of LLMs against Jailbreak Attacksby Kexin Chen, Yi Liu, Dongxia…
LLM-PCGC: Large Language Model-based Point Cloud Geometry Compressionby Yuqi Ye, Wei GaoFirst submitted to arxiv…
LLMI3D: MLLM-based 3D Perception from a Single 2D Imageby Fan Yang, Sicheng Zhao, Yanhao Zhang,…
On Effects of Steering Latent Representation for Large Language Model Unlearningby Dang Huu-Tien, Trung-Tin Pham,…
LLMs are Not Just Next Token Predictorsby Stephen M. Downes, Patrick Forber, Alex GrzankowskiFirst submitted…
SCENE: Evaluating Explainable AI Techniques Using Soft Counterfactualsby Haoran Zheng, Utku PamuksuzFirst submitted to arxiv…
COMMENTATOR: A Code-mixed Multilingual Text Annotation Frameworkby Rajvee Sheth, Shubh Nisar, Heenaben Prajapati, Himanshu Beniwal,…
Language Model Can Listen While Speakingby Ziyang Ma, Yakun Song, Chenpeng Du, Jian Cong, Zhuo…
DeMansia: Mamba Never Forgets Any Tokensby Ricky FangFirst submitted to arxiv on: 4 Aug 2024CategoriesMain:…