6 papers · 1 filter
PersonaMem-v2: Towards Personalized Intelligence via Learning Implicit User Personas and Agentic Memory
Bowen Jiang, Yuan Yuan, Maohao Shen +13
Personalization is one of the next milestones in advancing AI capability and alignment. We introduce PersonaMem-v2, the state-of-the-art dataset for LLM personalization that simula…
Know Me, Respond to Me: Benchmarking LLMs for Dynamic User Profiling and Personalized Responses at Scale
Bowen Jiang, Zhuoqun Hao, Young-Min Cho +6
Large Language Models (LLMs) have emerged as personalized assistants for users across a wide range of tasks -- from offering writing support to delivering tailored recommendations…
Talking Point based Ideological Discourse Analysis in News Events
Nishanth Nakshatri, Nikhil Mehta, Siyi Liu +4
Analyzing ideological discourse even in the age of LLMs remains a challenge, as these models often struggle to capture the key elements that shape real-world narratives. Specifical…
On Reference (In-)Determinacy in Natural Language Inference
Sihao Chen, Chaitanya Malaviya, Alex Fabrikant +4
We revisit the reference determinacy (RD) assumption in the task of natural language inference (NLI), i.e., the premise and hypothesis are assumed to refer to the same context when…
Dense X Retrieval: What Retrieval Granularity Should We Use?
Tong Chen, Hongwei Wang, Sihao Chen +5
Dense retrieval has become a prominent method to obtain relevant context or world knowledge in open-domain NLP tasks. When we use a learned dense retriever on a retrieval corpus at…
Dynamic Clue Bottlenecks: Towards Interpretable-by-Design Visual Question Answering
Xingyu Fu, Ben Zhou, Sihao Chen +2
Recent advances in multimodal large language models (LLMs) have shown extreme effectiveness in visual question answering (VQA). However, the design nature of these end-to-end model…