VIF-Bench is introduced, a benchmark of 1,241 tasks designed to assess the edge of model capabilities in this joint setting in which multiple references must be composed under multiple and heterogeneous visual-instruction images, and uncover three findings.
Yuta Oshima, Masakazu Yoshimura, Masahiro Suzuki et al.· 0 citations
This work proposes AutoRef, which optimizes the harness automatically while keeping both models frozen: a coding agent iteratively rewrites the harness code, and discovers AutoRef-Harness, which improves the open-weight FLUX.
Yuta Oshima, Ku Onoda, Yusuke Iwasawa et al.· 0 citations
A symbolic-attribute oracle shows that CoT can improve counting once ground-truth attributes are supplied as text, while a single-object probe-vs-decode check shows that hard attributes can be linearly recoverable from hidden states yet difficult for the model itself to output.
Readout Feedback (RoFB), a test-time intervention that converts intermediate predictions into token-wise pairwise coupling forces injected into the latent dynamics, is introduced, suggesting that closed-loop steering of latent dynamics can serve as a complementary inference-time control mechanism for recurrent reasonin...
Shunsuke Kamiya, Masanori Koyama, Seongcheol Jeong et al.· 0 citations
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