activity
20242026
collaborators

43 papers

cs.CV2026

Ground3D-LMM: Fine-Grained 3D Point Grounding and Spatial Reasoning with LMM

Amol Harsh, Zongyan Han, Jean Lahoud +5

Natural-language queries about 3D environments become actionable when responses are verifiable and metric. Verifiability requires explicit grounding to the referred 3D region, whil…

cs.CV2026

Ask, Solve, Generate: Self-Evolving Unified Multimodal Understanding and Generation via Self-Consistency Rewards

Ritesh Thawkar, Shravan Venkatraman, Omkar Thawakar +5

Most unified large multimodal models (LMMs) that support both visual understanding and image generation still rely on curated post-training supervision, such as human annotations,…

cs.CV2026

Paying More Attention to Visual Tokens in Self-Evolving Large Multimodal Models

Shravan Venkatraman, Ritesh Thawkar, Omkar Thawakar +4

Recently, self-evolving large multimodal models (LMMs) have received attention for improving visual reasoning in a purely unsupervised setting. However, multi-role self-play and se…

cs.CV2026

A Benchmark for Omni-Modal Reasoning in Long Videos

Mohammed Irfan Kurpath, Jaseel Muhammad Kaithakkodan, Jinxing Zhou +12

Long-form omni-modal video understanding requires integrating vision, speech, and ambient audio with coherent long-context reasoning. Existing video benchmarks often trade off temp…

cs.CV2026

EvoLMM: Self-Evolving Large Multimodal Models with Continuous Rewards

Omkar Thawakar, Shravan Venkatraman, Ritesh Thawkar +5

Recent advances in large multimodal models (LMMs) have enabled impressive reasoning and perception abilities, yet most existing training pipelines still depend on human-curated dat…

cs.CV2026

MAviS: A Multimodal Conversational Assistant For Avian Species

Yevheniia Kryklyvets, Mohammed Irfan Kurpath, Sahal Shaji Mullappilly +5

Fine-grained understanding and species-specific multimodal question answering are vital for advancing biodiversity conservation and ecological monitoring. However, existing multimo…