6 papers indexed here
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
Large vision-language models (LVLMs) exhibit strong multimodal in-context learning (ICL) capabilities, yet this ability degrades substantially as model size decreases. Knowledge distillation offers a natural way to bridge this gap, but existing methods primarily align output distributions or hidden representations dire...
Graph-Conditioned On-Policy Agent Distillation is introduced, which enriches an off-the-shelf teacher's scoring context with execution evidence, and indexes repeated teacher executions by shared states while preserving complete successful and failed histories.
ReaLVR is proposed, which brings visual-evidence supervision to the model's own free-running latent trajectories, and is the first to scale visual reasoning in latent space, showing that the framework continues to deliver robust improvements at frontier model scales up to 235B.
ForGE is proposed, a unified framework for adapting frozen models through per-query routing over a joint action space that spans both support form and thinking depth and improves accuracy at 42-45% lower token cost on both main hosts.
This work introduces TempFinRAG, a point-in-time evaluation protocol built from public filings and XBRL facts, and introduces TempFinQA, a point-in-time evaluation protocol built from public filings and XBRL facts, and evaluates the framework on complementary evidence-grounded, numerical, conversational, and multi-tabl...
This work injects two complementary semantic priors into Visual prompt tuning, a cascaded scheme that integrates both priors throughout ViT adaptation, and proposes a cascaded scheme that integrates both priors throughout ViT adaptation.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
