Gemini
By M. Yates. SIGGRAPH ASIA Animations, 2009
595 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Strategy and Management
View Paper: https://www.semanticscholar.org/paper/95a23aaee1687f847a34998dd6f3775d96712722
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Francesco Croce
- Maksym Andriushchenko
- Nicolas Flammarion
- Vikash Sehwag
- Edoardo Debenedetti
- George Pappas
- Dafna Shahaf
- Gabriel Stanovsky
Citations in the corpus
- State of What Art? A Call for Multi-Prompt LLM Evaluation (2023, background): “While there are reasons to withhold instructions (e.g., avoid potential leakage), this practice exacerbates the challenge of meaningful comparative evaluation.”
- WebThinker: Empowering Large Reasoning Models with Deep Research Capability (2025, unknown): “Therefore, the deep integration of LRM’s reasoning capabilities with web information exploration has become a practical demand, which has sparked a series of deep research initiatives by OpenAI [36], xAI Grok3 [14], and Google Gemini [12].”
- JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models (2024, background): “Two months after releasing the preliminary version of JailbreakBench on arXiv, researchers in the field have already started using our jailbreak artifacts (Peng et al., 2024; Abdelnabi et al., 2024), jailbreak judge prompt (Zheng et al., 2024), and the JBB-Behaviors dataset (Xiong et al., 2024; Ardi”
- AndroidWorld: A Dynamic Benchmarking Environment for Autonomous Agents (2024, unknown): “More recent work tends to leverage off-the-shelf foundational models [50, 51, 52] with in-context learning (ICL) and fine-tuning applied to mobile [41, 18, 56, 61, 68, 4], desktop web [70, 9, 73, 24], and desktop OS [58, 66, 59].”
- Detecting hallucinations in large language models using semantic entropy (2024, unknown): “We measure entailment using both general-purpose LLMs and natural language inference (NLI) tools developed specifically for detecting entailment for which we show direct evaluations in Supplementary Tables 2 and 3 and Supplementary Fig.”