# apple-aiml-research/ml-lensvlm > Official code for LensVLM, a 9B Vision Language Model that scans compressed page images and selectively expands only relevant pages via a read_page tool to answer questions. - Magnitude: 1.1 out of 10 — Cooling - Stars: 71 total · +0 stars today, ≈ 4 by evening - Star trust: star growth looks organic - Category: Language models · Language: Python · Created: 2026-09-22 · Last push: 2026-09-22 - GitHub: https://github.com/apple-aiml-research/ml-lensvlm · Homepage: https://arxiv.org/abs/2605.07019 · Page: https://gitnova.dev/en/r/apple-aiml-research/ml-lensvlm ## Useful for - Run the bundled HotpotQA demo to inspect the multi-turn page-selection trajectory - Prepare an eval set from HotpotQA/NQ/Musique with 5x/10x/15x compression and distractors - Evaluate answer accuracy and page-selection metrics with an LLM judge ## Why it’s here - 0 stars so far today, about 4 expected by the end of the day. - The repository is 4 days old and already has 71 stars. With less than two weeks of history, there's no usual pace to compare the spike against yet. - Top new repositories this week: #190. ## Star trust Star growth looks organic. Star-trust labels are heuristics based on the repository’s behavior, not a check of every stargazer. ## Numbers - Forks: 5 - Issues and pull requests: 0 - Watchers: 0 - Average over the last week: 15 per day - Usual pace: too little history (under two weeks) - Stars in the last hour (measured): 0 ## Stars per day, last 7 days (oldest → newest, today is partial) 2026-09-20 … 2026-09-26: 0, 0, 6, 39, 21, 5, 0 ## Spotted in now - Top new repositories this week: #190 ## More in this category 1. **ollaya-dev/ollaya** — 6.9 · Early signal · Language models · Rust · +0 stars today, ≈ 129 by evening A local runtime for decision models: pulls and serves classification and routing models behind a TypeSafe-compatible API. Like Ollama, but for models that return probabilities instead of text. Full card: https://gitnova.dev/en/r/ollaya-dev/ollaya.md 2. **NVIDIA/Model-Optimizer** — 6.4 · Breakout · Language models · Python · +0 stars today, ≈ 248 by evening NVIDIA library for compressing and accelerating models: quantization, pruning, distillation, NAS and speculative decoding with export to TensorRT-LLM, vLLM, SGLang. For ML engineers preparing models for deployment. Full card: https://gitnova.dev/en/r/NVIDIA/Model-Optimizer.md 3. **nokia-applied-research/AnyJev** — 5.3 · Early signal · Language models · Python · +0 stars today, ≈ 144 by evening Turns any LLM into a decision model with typed questions (choice, yes/no, score) that return real probabilities read from the next-token distribution, without training. L0 removes position and label-prior bias; L1 adds temperature… Full card: https://gitnova.dev/en/r/nokia-applied-research/AnyJev.md 4. **Badtheorylabs/interference-search** — 4.7 · Early signal · Language models · Python · +0 stars today, ≈ 77 by evening A search method that reasons over explicit states instead of a language model's linear transcript: many branches expand at once, duplicates merge, dead ends are dropped by a trained judge, and survivors advance together. The repo ships… Full card: https://gitnova.dev/en/r/Badtheorylabs/interference-search.md 5. **Liuziyu77/Valen** — 4.4 · Early signal · Language models · Python · +0 stars today, ≈ 57 by evening A multimodal decision model built on a Qwen3.5-0.8B/2B backbone: it takes text, images and video with an instruction and returns probabilities over supplied candidates without generating answer tokens. The repo includes model code, data… Full card: https://gitnova.dev/en/r/Liuziyu77/Valen.md --- Magnitude (0–10) measures how fast and how unusually interest in a repository is growing right now. It is not a quality score. Days are UTC. “So far today” is a fact; “expected by the end of the day” is a forecast. Summaries and use cases are written by an LLM (DeepSeek V4.1 Flash) from the README and may be inaccurate: verify specific claims (benchmarks, speed, hardware) in the repository itself. Data as of 2026-09-26 03:18 UTC, updated every 30 minutes.