1 citations · 1 across the 8 of their papers we have counts for
9 papers
Reinforcement Learning with Comparative Evidence for Social Intelligence
Keane Ong, Yuriel Ryan, Sabri Boughorbel +9
Developing socially intelligent AI remains heavily dependent on human-annotated data, limiting the scale and breadth of social understanding models can acquire. Methods that derive…
Video Active Perception: Effective Inference-Time Long-Form Video Understanding with Vision-Language Models
Martin Q. Ma, Willis Guo, Aditya Agrawal +4
Large vision-language models (VLMs) have advanced multimodal tasks such as video question answering (QA). However, VLMs face the challenge of selecting frames effectively and effic…
Act2See: Emergent Active Visual Perception for Video Reasoning
Martin Q. Ma, Yuxiao Qu, Aditya Agrawal +4
Vision-Language Models (VLMs) typically rely on static initial frames for video reasoning, restricting their ability to incorporate essential dynamic information as the reasoning p…
CTM-AI: A Blueprint for General AI Inspired by a Model of Consciousness
Haofei Yu, Yining Zhao, Lenore Blum +2
Despite remarkable advances, today's AI systems remain narrow in scope, falling short of the flexible, adaptive, and multisensory intelligence that characterizes human capabilities…
ORION: Teaching Language Models to Reason Efficiently in the Language of Thought
Kumar Tanmay, Kriti Aggarwal, Paul Pu Liang +1
Large Reasoning Models (LRMs) achieve strong performance in mathematics, code generation, and task planning, but their reliance on long chains of verbose "thinking" tokens leads to…
Learn Globally, Speak Locally: Bridging the Gaps in Multilingual Reasoning
Jaedong Hwang, Kumar Tanmay, Seok-Jin Lee +5
Large Language Models (LLMs) have achieved strong performance in domains like mathematics, factual question answering, and code generation, yet their ability to reason on these tas…
Deriving Strategic Market Insights with Large Language Models: A Benchmark for Forward Counterfactual Generation
Keane Ong, Rui Mao, Deeksha Varshney +3
Counterfactual reasoning typically involves considering alternatives to actual events. While often applied to understand past events, a distinct form-forward counterfactual reasoni…
Language Models' Factuality Depends on the Language of Inquiry
Tushar Aggarwal, Kumar Tanmay, Ayush Agrawal +3
Multilingual language models (LMs) are expected to recall factual knowledge consistently across languages, yet they often fail to transfer knowledge between languages even when the…
Benchmarking Vision, Language, & Action Models on Robotic Learning Tasks
Pranav Guruprasad, Harshvardhan Sikka, Jaewoo Song +2
Vision-language-action (VLA) models represent a promising direction for developing general-purpose robotic systems, demonstrating the ability to combine visual understanding, langu…