2 citations · 4 across the 5 of their papers we have counts for
6 papers
MiniCorp: The Last Mile to an AI Agent Corporation
Jingying Zeng, Zhenwei Dai, Jinning Li +6
The last mile toward enterprise AGI is a company that runs itself. Training and adapting such agents require longitudinal enterprise data, which remain scarce, costly to acquire, a…
LongMemEval-V2: Evaluating Long-Term Agent Memory Toward Experienced Colleagues
Di Wu, Zixiang Ji, Asmi Kawatkar +4
Long-term memory is crucial for agents in specialized web environments, where success depends on recalling interface affordances, state dynamics, workflows, and recurring failure m…
CustomerSim: Benchmarking and Aligning Multimodal Language Models as Retail User Simulators
Yada Pruksachatkun, Yixin Wan, Xingrun Chen +2
We present CustomerSim, an environment and benchmark to evaluate the extent to which Multimodal Large Language Models (MLLMs) can simulate realistic, persona-driven customer behavi…
Customize Multi-modal RAI Guardrails with Precedent-based predictions
Cheng-Fu Yang, Thanh Tran, Christos Christodoulopoulos +3
A multi-modal guardrail must effectively filter image content based on user-defined policies, identifying material that may be hateful, reinforce harmful stereotypes, contain expli…
The Amazon Nova Family of Models: Technical Report and Model Card
Amazon AGI, Aaron Langford, Aayush Shah +783
We present Amazon Nova, a new generation of state-of-the-art foundation models that deliver frontier intelligence and industry-leading price performance. Amazon Nova Pro is a highl…
Can Small Language Models Help Large Language Models Reason Better?: LM-Guided Chain-of-Thought
Jooyoung Lee, Fan Yang, Thanh Tran +4
We introduce a novel framework, LM-Guided CoT, that leverages a lightweight (i.e., <1B) language model (LM) for guiding a black-box large (i.e., >10B) LM in reasoning tasks. Specif…