Model Detail
POCKET-EN-GGUF
—POCKET-EN-GGUF is a large language model with 36B parameters released by FINAL-Bench. The model is registered under the text-generation pipeline tag on Hugging Face, distributed under the permissive apache-2.0 license.
POCKET-EN-GGUF ships with 36B parameters, distributed as a quantized weight variant for lower-VRAM inference. The apache-2.0 license is permissive, allowing commercial deployment and derivative work without per-seat fees, though attribution requirements still apply.
POCKET-EN-GGUF is best fit for general-purpose chat and instruction-following workloads. Treat this as a starting matrix rather than a benchmark verdict — the right deployment usually depends on the specific evaluation suite that mirrors your workload.
zPocket: Better Pocket Finding with Frozen Co-Folding Features
arXiv:2610.17696v1 Announce Type: cross Abstract: Identifying protein-ligand binding sites (pockets) is important for understanding protein function and developing drugs. However, no public method has leveraged co-folding models for novel pocket prediction; furthermore, this task lacks a suitable be
Auditable Algebraic Counting Field for Cryptic-Pocket Detection from Apo Structures
arXiv:2610.00988v1 Announce Type: new Abstract: Cryptic ligand-binding pockets are not apparent in experimentally determined apo structures, making them difficult to identify from unbound receptor geometry. A complementary challenge is to make the structural measurements and learned evidence behind
Budgeted Quotient-Residual Guidance for Frozen Pocket-Conditioned Molecular Diffusion
arXiv:2609.31222v1 Announce Type: new Abstract: Pocket-conditioned molecular diffusion updates ambient atom coordinates, but many lead-optimization objectives are expressed on quotient features such as distances, contacts, and anchored substructures. We introduce budgeted quotient-residual guidance
Pocket-STVG: lightweight architecture for Spatio-Temporal Video Grounding
arXiv:2609.31135v1 Announce Type: cross Abstract: Spatio-Temporal Video Grounding (STVG) aims to localize the spatio-temporal tube in a video corresponding to a natural language query. While recent methods achieve strong performance in fully supervised, weakly supervised, and zero-shot settings, the
India’s Pocket FM doubles revenue run rate to $500M as AI powers 93% of audio content
Pocket FM uses AI to produce 99% of its new content, helping make content production about 80 times cheaper.
NEAT-POCKET: Pocket-Conditioned Autoregressive 3D Molecular Generation with a Neighborhood-Guided Set Transformer
arXiv:2609.05097v1 Announce Type: cross Abstract: AI-driven de novo molecular design offers a promising route to accelerate early-stage drug discovery by generating novel ligands directly within target protein binding pockets. We present NEAT-POCKET, a pocket-conditioned extension of the autoregress
