Large Language Model
Easy-to-Hard Generalization: Scalable Alignment Beyond Human Supervision
This raises a challenging research question: How can we keep improving the systems when their capabilities have surpassed the levels of humans?
MMScan: A Multi-Modal 3D Scene Dataset with Hierarchical Grounded Language Annotations
Built upon existing 3D scanning data, the resulting multi-modal 3D dataset encompasses 1.4M
Supplementary material for CTIBench: A Benchmark for Evaluating LLMs in Cyber Threat Intelligence 1 Dataset Documentations 1 1.1 Hosted URLs
This task assesses the LLMs' ability to evaluate the severity of This task tests the LLMs' capability to The dataset consists of 5 TSV files, each corresponding to a different task. "Prompt" column used to pose questions to the LLM. Most files also include a "GT" column that Do not distribute. of LLMs to understand and analyze various aspects of open-source CTI. The dataset includes URLs indicating the sources from which the data was collected. A permanent DOI identifier is associated with the dataset: DOI: AI4Sec (2024).
SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering John Y ang Carlos E. Jimenez
SWE-bench test instances (SWE-bench Lite) to analyze our ACI design choices.
Selective Generation for Controllable Language Models
Trustworthiness of generative language models (GLMs) is crucial in their deployment to critical decision making systems.
Using Set Operations to Evaluate the Lexical and Semantic Robustness of Language Models
Set theory is foundational to mathematics and, when sets are finite, to reasoning about the world. An intelligent system should perform set operations consistently, regardless of superficial variations in the operands.
Optimus-1: Hybrid Multimodal Memory Empowered Agents Excel in Long-Horizon Tasks
In this paper, we propose a Hybrid Multimodal Memory module to address the above challenges.