arXiv:2610.00111v1 Announce Type: new
Abstract: Model judges now supervise multimodal systems at scale, filtering training data, selecting outputs, and supplying the reward that shapes multimodal rea...
By Rasul Khanbayov, Hasan Kurban
The paper demonstrates that vision‑language models’ refusal behavior is heavily influenced by whether an image is attached to a request, even when the image is blank or unreadable. Attaching such an image shifts refusal scores by large margins for borderline‑benign prompts while leaving genuinely neutral instructions largely unchanged. This effect varies with image properties, persists across checkpoints, and is not mitigated by explicit instructions to ignore the image.
By Haoyu Zhang, Yi Feng, Hanwen Liu, Shibo Zheng, Zhuoxi Wang, Yang Chen, Haowen Xu, Xiangchen Guan, Mohammad Zandsalimy, Shanu Sushmita
arXiv:2607. 23191v2 Announce Type: replace Abstract: Fine-tuned code LLMs are often conditioned on a design-intent header to steer parametric CAD generation, but whether the model reads that header's content has been tested neither under execution-level scoring nor with a causal control.
By Yang Xiao
arXiv:2609.06872v1 Announce Type: new
Abstract: When a user asks an assistant to forget a record, the test is whether the memory now matches the state it would hold if the record had never been store...
By Vishwajith Ramesh
arXiv:2608.31016v1 Announce Type: cross
Abstract: Ambient AI scribes draft clinical notes, and published audits find their dominant error is omission: information the encounter established that the n...
By Sebastian Fox, Luke Markham, Ryan Lail, Michael Karotsieris
The paper investigates how providing execution traces to multimodal judges in agentic video‑generation systems can bias their verdicts. On a benchmark of 109 two‑event clips, traces that falsely report successful tool calls cause large‑language‑model judges to incorrectly accept 78–90 % of failures, while contradictory traces lead to 100 % rejection of correct clips. The effect persists even when judges are instructed to consider only the video frames, indicating that the vulnerability stems from the judges’ learned trust in tool logs rather than the visual content itself.
By Jian Xu