…Notably, the noise diffusion stage is trained exclusively on abundant, unpaired target-domain images, greatly improving data efficiency . Comprehensive theoretical and empirical analysis demonstrates that DRDD is broadly compatible with mainstream diffusion…
…Venkata Pushpak Teja Menta Abstract A self-contained text-to-speech to speech-to-text flywheel approach significantly improves niche-domain Indic automatic speech recognition performance through synthetic data generation and low…
…However, the performance of consistency-distilled models often degrades as more sampling steps are allocated at test time, limiting their effectiveness for any-step video diffusion. This limitation arises because consistency distillation…
…Ideally, replacing a textual question with its rendered-image counterpart should leave model performance essentially unaffected. In practice, however, such modality substitution induces dramatic performance degradation. We attribute this " carrier sensitivity " issue…
…AI-generated summary While recent advancements in multimodal language models have enabled image generation from expressive multi-image instructions, existing methods struggle to maintain performance under complex interleaved instructions . This limitation stems…
…Xingyuan Hua , , Abstract Agents use variational inference to evaluate exploratory actions and selectively explore only when uncertainty is high, improving performance on text-based and GUI-based benchmarks. AI-generated summary Recent…
…numerical regression performance on long-tailed distributions through batch-level comparison-based supervision. AI-generated summary Multimodal large language models (MLLMs) struggle with numerical regression under long-tailed target distributions. Token-level…
…across four target models from three families. On LongBench v2, the two-stage recipe largely closes the Stage 1 gap on multi-document reasoning while preserving Code-Debug performance. View arXiv page…
…However, performing this well requires delegation intelligence : the ability to decompose complex tasks, determine when and what to delegate, and integrate returned results into the ongoing workflow. Training data for this capability…
…instruction adherence and general omni-modal captioning performance. View arXiv page View PDF Project page GitHub 12 Add to collection Community OmniCap-IF targets instruction-following in omni-modal video captioning, where…