Papers on skulldchttps://skulldc.net/tags/papers/Recent content in Papers on skulldcHugoen-usFri, 06 Nov 2026 10:26:06 +0000DPDM routes agent decisions through one frozen conditional predictor instead of promptinghttps://skulldc.net/2026/11/dpdm-routes-agent-decisions-through-one-frozen-conditional-predictor-i/Fri, 06 Nov 2026 10:26:06 +0000https://skulldc.net/2026/11/dpdm-routes-agent-decisions-through-one-frozen-conditional-predictor-i/A paper proposes DPDM, which pairs a language model encoder with a frozen pretrained predictor so agents learn from deployment history without any weight updates.NEO-VLA drops the vision encoder so action policies can read visual features at any depthhttps://skulldc.net/2026/11/neo-vla-drops-the-vision-encoder-so-action-policies-can-read-visual-fe/Thu, 05 Nov 2026 10:25:39 +0000https://skulldc.net/2026/11/neo-vla-drops-the-vision-encoder-so-action-policies-can-read-visual-fe/A paper from MMLab@NTU argues that vision-language-action models lose action-critical detail in their visual encoders and proposes NEO-VLA, an encoder-free design.FactEmbed factorizes MLLM embeddings for composed image retrievalhttps://skulldc.net/2026/11/factembed-factorizes-mllm-embeddings-for-composed-image-retrieval/Wed, 04 Nov 2026 20:26:21 +0000https://skulldc.net/2026/11/factembed-factorizes-mllm-embeddings-for-composed-image-retrieval/A KAIST AI paper makes an MLLM imagine the requested image edit through factorized latents before building retrieval embeddings, and reuses those latents for cheap reranking.