229 citations · 359 across the 31 of their papers we have counts for
26 papers
GameBench: Evaluating Strategic Reasoning Abilities of LLM Agents
Anthony Costarelli, Mat Allen, Roman Hauksson +6
Large language models have demonstrated remarkable few-shot performance on many natural language understanding tasks. Despite several demonstrations of using large language models…
AIM: Let Any Multi-modal Large Language Models Embrace Efficient In-Context Learning
Jun Gao, Qian Qiao, Ziqiang Cao +2
In-context learning (ICL) facilitates Large Language Models (LLMs) exhibiting emergent ability on downstream tasks without updating billions of parameters. However, in the area of…
A Survey of Generative Search and Recommendation in the Era of Large Language Models
Yongqi Li, Xinyu Lin, Wenjie Wang +6
With the information explosion on the Web, search and recommendation are foundational infrastructures to satisfying users' information needs. As the two sides of the same coin, bot…
JobFormer: Skill-Aware Job Recommendation with Semantic-Enhanced Transformer
Zhihao Guan, Jia-Qi Yang, Yang Yang +3
Job recommendation aims to provide potential talents with suitable job descriptions (JDs) consistent with their career trajectory, which plays an essential role in proactive talent…
Target-constrained Bidirectional Planning for Generation of Target-oriented Proactive Dialogue
Jian Wang, Dongding Lin, Wenjie Li
Target-oriented proactive dialogue systems aim to lead conversations from a dialogue context toward a pre-determined target, such as making recommendations on designated items or i…
Generative Cross-Modal Retrieval: Memorizing Images in Multimodal Language Models for Retrieval and Beyond
Yongqi Li, Wenjie Wang, Leigang Qu +3
The recent advancements in generative language models have demonstrated their ability to memorize knowledge from documents and recall knowledge to respond to user queries effective…