Anudeepsekhar Bolimera — accepted AI-conference papers

2026

MetaVLA: Unified Meta Co-Training for Efficient Embodied Adaptation

Chen Li, Zhantao Yang, Han Zhang, Fangyi Chen, Chenchen Zhu, Anudeepsekhar Bolimera +1

ICLR 2026poster

Vision–Language–Action (VLA) models show promise in embodied reasoning, yet remain far from true generalists—they often require task-specific fine-tuning, incur high compute costs, and generalize poorly to unseen tasks. We propose MetaVLA, a unified, backbone-agnostic post-training framework for eff…

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2026

STELAR-VISION: Self-Topology-Aware Efficient Learning for Aligned Reasoning in Vision

Chen Li, Han Zhang, Zhantao Yang, Fangyi Chen, Zihan Wang, Anudeepsekhar Bolimera +1

AAAI 2026technical

Vision-language models (VLMs) have made significant strides in reasoning, yet they often struggle with complex multimodal tasks and tend to generate overly verbose outputs. A key limitation is their reliance on chain-of-thought (CoT) reasoning, despite many tasks benefiting from alternative topologi

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