GRASP is a large-scale dataset and benchmark for social reasoning grounded in gaze and gesture events in multi-person videos, with Social Grounding Reward (SGR) proposed to improve model performance on GRASP-Bench.
Towards social ai: A survey on understanding social interactions
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SocialDirector uses spatiotemporal actor masking and directional reweighting on cross-attention maps to reduce actor-action mismatches and improve target-directed interactions in generated multi-person videos.
SAVOIR combines prospective expected utility valuation with Shapley values for fair credit assignment in social dialogue RL, achieving SOTA on SOTOPIA where a 7B model matches or exceeds GPT-4o and Claude-3.5-Sonnet.
citing papers explorer
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GRASP: Learning to Ground Social Reasoning in Multi-Person Non-Verbal Interactions
GRASP is a large-scale dataset and benchmark for social reasoning grounded in gaze and gesture events in multi-person videos, with Social Grounding Reward (SGR) proposed to improve model performance on GRASP-Bench.
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SocialDirector: Training-Free Social Interaction Control for Multi-Person Video Generation
SocialDirector uses spatiotemporal actor masking and directional reweighting on cross-attention maps to reduce actor-action mismatches and improve target-directed interactions in generated multi-person videos.
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SAVOIR: Learning Social Savoir-Faire via Shapley-based Reward Attribution
SAVOIR combines prospective expected utility valuation with Shapley values for fair credit assignment in social dialogue RL, achieving SOTA on SOTOPIA where a 7B model matches or exceeds GPT-4o and Claude-3.5-Sonnet.