not much happened today
**Prime Intellect** released **verifiers v1**, a redesigned environment stack for **agentic reinforcement learning** and evaluations, improving efficiency by storing rollout traces as **message DAGs** to reduce…
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The Graph That Should Be Front-Page News
Article URL: https://www.lyrebirddreaming.com/post/the-graph-that-should-be-front-page-news Comments URL: https://news.ycombinator.com/item?id=48888331 Points: 5 # Comments: 3
Dean was so right… looks like I've gotta hit the Talmud too
Dean was so right…looks like I've gotta hit the Talmud tooSGN20 U5G: @AngelicaOung @teortaxesTex feo-taxes is most likely a closeted zionist
Beavis Ultrasound PnP ISA Sound Card Replica
Article URL: https://github.com/schlae/BeavisUltrasound Comments URL: https://news.ycombinator.com/item?id=48888193 Points: 12 # Comments: 2
KronQ: LLM Quantization via Kronecker-Factored Hessian
Post-training quantization (PTQ) is a widely adopted technique for compressing large language models (LLMs) without retraining. Existing second-order PTQ methods, including GPTQ, construct quantization objectives exclusively…
Prompt-engineering paper accepted to ICML [R]
"Verbalized Sampling: How to Mitigate Mode Collapse and Unlock LLM Diversity" This paper was accepted to ICML this year. Its main idea is a very simple…
RT goldenlabubuwatch: Of course not less than 2 days after raising usd4bn here comes Zhipu founder with a letter to employees saying commercialization…
RT goldenlabubuwatchOf course not less than 2 days after raising usd4bn here comes Zhipu founder with a letter to employees saying commercialization goes down the priority…
good use case!
good use case!Pauline P. Narvas: Use @ChatGPTapp Work for your most important tasks ⚽️
Flash-MSA: Accelerating Million-Token Training With Sparse Attention Kernels
submitted by /u/nullc [link] [comments]
Bytedance continues to chase GDM "Reasoning" in pure image generation, trained with – you guessed it! – another variant of GRPO.
Bytedance continues to chase GDM"Reasoning" in pure image generation, trained with – you guessed it! – another variant of GRPO.DailyPapers: ByteDance just released UniVR-34B on Hugging…
ChatGPT Work is so good, very proud of the team and excited for people to explore what’s possible
ChatGPT Work is so good, very proud of the team and excited for people to explore what’s possibleVictor E. Nunez: a lot of people haven’t realized…
Long-Horizon-Terminal-Bench: Testing the Limits of Agents on Long-Horizon Terminal Tasks with Dense Reward-Based Grading
AI agents have become capable of autonomously completing short, well-specified tasks. However, existing terminal benchmarks largely focus on simple problems that finish within minutes and are…
Count Binface
Article URL: https://countbinface.com Comments URL: https://news.ycombinator.com/item?id=48887753 Points: 52 # Comments: 14
comprisk: A scikit-learn-compatible Python toolkit for competing-risks survival analysis
arXiv:2607.09431v1 Announce Type: cross Abstract: Medical time-to-event data are frequently subject to competing risks, where the occurrence of one terminal event precludes the others and standard…
Similarity search generalisation in contrastive learning with InfoNCE loss
arXiv:2607.09405v1 Announce Type: cross Abstract: Similarity search is a primary application of embedding models trained by contrastive learning. For one of the most popular contrastive learning…
Influence Diagnostics in High-dimensional M-estimation: Precise Asymptotics
arXiv:2607.09250v1 Announce Type: new Abstract: The impact of a given training point on a statistical model is classically measured through its leave-one-out influence, which quantifies the…
Solving Stochastic Fixed-Point Equations with High Probability
arXiv:2607.09097v1 Announce Type: cross Abstract: We study stochastic fixed-point equations $mathbf{T}(mathbf{x}) = mathbf{x}$ over normed spaces $(mathcal{E}, |cdot|)$, where the operator $mathbf{T}$ is nonexpansive or contractive…
Achieving Almost Exact Recovery in Almost Quadratic Time: Rank-Based Graph Matching via Local Tree Correlation Tests
arXiv:2607.09087v1 Announce Type: cross Abstract: This paper studies graph matching under the correlated $text{ErdH{o}s-R'{e}nyi}$ (ER) graph pair model. This model first samples an $mathrm{ER}(n,frac{lambda}{ns})$ base graph,…
Principles of Lipschitz continuity in neural networks
arXiv:2602.04078v2 Announce Type: replace-cross Abstract: Deep learning has achieved remarkable success across a wide range of domains, significantly expanding the frontiers of what is achievable in…
Optimal Top-$k$ Identification from Pairwise Comparisons
arXiv:2607.08979v1 Announce Type: cross Abstract: We study the active learning problem of fixed-confidence top-$k$ identification from noisy pairwise comparisons. In this problem, an algorithm sequentially chooses…
Cluster and then Embed: A Modular Approach for Visualization
arXiv:2509.03373v2 Announce Type: replace-cross Abstract: Dimensionality reduction methods such as t-SNE and UMAP are popular methods for visualizing data with a potential (latent) clustered structure. They…
Stochastic Linear Bandits with Partially Observed Actions
arXiv:2607.08971v1 Announce Type: cross Abstract: The stochastic linear bandit, where actions are represented as vectors and rewards are linear, is a central paradigm for sequential decision…
Spectrally Deconfounded Gradient Boosting
arXiv:2607.09371v1 Announce Type: new Abstract: Flexible machine-learning methods can be sensitive to hidden confounding: they may learn associations induced by unobserved confounders rather than stable signals.…
Characterization of the basin of convexity for multi-snapshot spike deconvolution via variable projection
arXiv:2607.09593v1 Announce Type: new Abstract: We study the problem of multi-snapshot spike deconvolution, where the goal is to recover the locations of sparse impulses from their…