Search: “index”

Correct Choices, Failed Sequences: Choice2Seq Benchmarks Correctness Retention Across Output Interfaces

arXiv:2610.16191v1 Announce Type: new Abstract: A model may select the correct answer yet fail to construct it through a sequence of local decisions. We introduce Choice2Seq, a diagnostic benchmark th

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Research

Deep Learning for Atmospheric Turbulence Mitigation: A Comparison Between GANs and Transformers

DGX agent

arXiv:2610.19274v1 Announce Type: cross Abstract: Atmospheric turbulence creates complex spatial and temporal distortions that significantly reduce image quality. This work compares two deep learning

researcharxiv-cs-cv

15 Oct 2026

Local Ai

Efficiently Learning To Reason or Not to Reason: Root-token Policy Optimization for Adaptive Thinking

arXiv:2610.17767v1 Announce Type: cross Abstract: Large reasoning models (LRMs) achieve strong performance by externalizing explicit reasoning traces before producing the answer, yet suffer from overt

local-aiarxiv-cs-ai

Graph-Enhanced Disease Trajectory Discovery and Temporal Endpoint Forecasting from Longitudinal Electronic Health Records

arXiv:2610.20502v1 Announce Type: new Abstract: Longitudinal electronic health records (EHRs) can reveal disease-progression structure, while useful forecasting requires leakage-controlled discovery,

great to see NYC pick up the slack when the federal government seems a bit lost.

great to see NYC pick up the slack when the federal government seems a bit lost. Anthropic should pause its initial public offering until it has fully addressed risks around artificial intelligence, a

safetygary-marcus--x

Hardware

Joint Subspace Sparse Attention for Efficient Long-Context Decoding

arXiv:2610.19026v1 Announce Type: new Abstract: Sparse attention reduces the KV-cache traffic that dominates long-context LLM decoding, but practical methods largely operate at coarse granularity. Tok

hardwarearxiv-cs-cl

ProCARE: Real-World Study Automation via Profile-Grounded Evidence Contracts

arXiv:2610.16175v1 Announce Type: new Abstract: Real-world studies (RWS) analyze routinely collected healthcare data, such as electronic health records and insurance claims, to estimate treatment effe

PXRD-Bench: How Close Are We to Determining Crystal Structures from Powder Diffraction?

arXiv:2610.16480v1 Announce Type: new Abstract: Determining crystal structures from powder X-ray diffraction (PXRD) would enable routine characterization of newly synthesized materials, including thos

Reducing the Gap Between Spatial and Space-Filling Curve Neighbors in 3D Point Cloud Segmentation

arXiv:2610.19530v1 Announce Type: new Abstract: As a lightweight and highly accurate method for nearest-neighbor search in 3D point clouds, approaches based on space-filling curves (SFC) have been pro

researcharxiv-cs-cv

ReferFlow: Beyond Final-Target Localization for Complex Referring Expressions

arXiv:2610.20352v1 Announce Type: new Abstract: Multimodal Large Language Models have made significant progress in referring expression comprehension (REC), yet most REC benchmarks still focus on fina

tutorialsarxiv-cs-cv

Rent-Seeking Language Models: Reward Models Set the Prices, Frequent Audits Curb the Rent

arXiv:2610.19832v1 Announce Type: new Abstract: Reward model overoptimization in RLHF is usually described as reward hacking. We recast it as rent-seeking: the policy, a firm, earns reward from a regu

safetyarxiv-cs-lg

Right Answer, Wrong Reason: Accuracy, Consistency, and Consensus Are Misleading Indicators of LLM Faithfulness in Clinical Decision Support

arXiv:2609.32817v2 Announce Type: replace Abstract: Clinical Large Language Models (LLMs) achieve strong medical-exam accuracy; however, a correct answer does not guarantee that the explanation names

safetyarxiv-cs-ai

STAMP as a topology-aware molecular language for fragment-level learning and editing

arXiv:2610.18438v1 Announce Type: cross Abstract: Molecular fragments provide chemically meaningful units, but existing molecular languages rarely make their locations and connections explicit for edi

StartLux-Decision: AutoThink Decision Models with Reinforcement Learning for Calibrated Deliberative Decisions

arXiv:2610.17309v1 Announce Type: cross Abstract: We introduce StartLux-Decision, decision models from 0.8B to 27B parameters that combine efficient single-pass prediction with adaptive, confidence-gu

Verification and Forward Invariance of Control Barrier Functions for Differential-Algebraic Systems

arXiv:2603.13509v2 Announce Type: replace-cross Abstract: Differential-algebraic equations (DAEs) arise in power networks, chemical processes, and multibody systems, where algebraic constraints encode

safetyarxiv-cs-ro

Video-Browser: Towards Open-web Agentic Video Browsing

model-releasesarxiv-cs-cv

arXiv:2512.23044v3 Announce Type: replace Abstract: Autonomous agents are shifting information seeking from passive retrieval toward proactive, open-ended research, yet this progress has largely bypas

W-JEPA: Wavelet Joint-Embedding Predictive Architecture for Wearable Activity Recognition

arXiv:2610.19411v1 Announce Type: new Abstract: A major challenge in wearable device activity recognition is the heterogeneity across datasets in sensor placement, channel count, sampling rate and sub

Constrained Diffusion Models with Primal-Dual Inference

arXiv:2606.17192v2 Announce Type: replace Abstract: This paper develops constrained diffusion models with primal-dual inference (PDI) to sample from optimal distributions of entropy-regularized optimi

safetyarxiv-cs-lg

CopyQuad: Quadrupedal Skill Transfer from a Single Side-View Video Without a Depth Model

arXiv:2610.16737v1 Announce Type: cross Abstract: Video-to-robot pipelines for quadrupedal imitation insert a learned lifting stage, either a monocular depth model or a per-clip 3D reconstruction, to

Deep Learning-based Mechanical Characterization of Synthetically Generated Plant Fibers under Transverse Compression

arXiv:2610.16529v1 Announce Type: new Abstract: Plant fibers are increasingly used as sustainable reinforcements in composites, but the intrinsic variability of their microstructure causes substantial

tutorialsarxiv-cs-cv

Deterministic denoising of long-duration gravitational-wave signal candidates with alpha-(de)blending

arXiv:2609.15308v1 Announce Type: cross Abstract: We present a deterministic machine-learning method for denoising candidate signals from all-sky searches for continuous gravitational waves from rotat

Distributional Regression for Arbitrary Response Variables Using ReLU Neural Networks

arXiv:2610.16142v1 Announce Type: cross Abstract: This paper develops a unified framework for distributional regression with arbitrary response variables. Rather than relying on scalar thresholds or E

Drafting Agents, Not Just Tokens: Speculative Recursive Self-Improvement for Agentic Systems

arXiv:2610.16491v1 Announce Type: new Abstract: Improving an agent through successive revisions requires balancing exploration and evaluation under a limited budget. A narrow search can miss useful se

agentsarxiv-cs-lg

Syntheses

Figma theme handoffs for existing application design systems

Human

A practical method for converting Figma theme evidence into an LLM handoff that fits an existing application and preserves accessibility.

figmadesign-systemsllm

Hardware

FlashMask-3: Efficient and Expressive Mask-Aware Distributed Attention

arXiv:2610.17901v1 Announce Type: new Abstract: Long-context training of large language and multimodal models couples structured attention masks (document, prefix-LM, share-question, sliding-window, b

hardwarearxiv-cs-lg

Hardware

Force Sensor-Based Picking Pattern Analysis and Two-Jaw Gripper Design for Cherry Tomato Robotic Harvesting in Greenhouse

arXiv:2610.18160v1 Announce Type: new Abstract: Robotic harvesting of cherry tomatoes in greenhouses remains challenging due to dense fruit clusters, delicate skin, and the need for gentle yet effecti

hardwarearxiv-cs-ro

Kwai Summary Attention V2 Technical Report

arXiv:2610.18654v1 Announce Type: new Abstract: Summary-token architectures such as Kwai Summary Attention (KSA) compress distant context into learnable Summary token per chunk, and hybrid variants in

Learning Dynamic Grasping

arXiv:2610.14848v1 Announce Type: new Abstract: Synthesizing believable 4D hand-object grasping sequences is important for character animation, extended reality, and embodied agents. Grasping requires

researcharxiv-cs-ro

MajorTOM:Elliot Pretrain, A Multi-Sensor, Multi-Temporal Pretraining Dataset for Earth Observation

model-releasesarxiv-cs-cv

arXiv:2610.18624v1 Announce Type: new Abstract: Pretraining generalist Earth observation foundation models requires data that combine several sensors, varied temporal sampling and, increasingly, text,

Masked Attention Pooling Is Invariant to Padding and Permutation: A Formal Proof in Lean

arXiv:2610.17132v1 Announce Type: new Abstract: Attention-based multiple instance learning (MIL) pools a variable-size bag of instance embeddings into one vector. In batched training, bags are padded

nanoflann: A Header-Only KD-Tree Library for Exact Nearest-Neighbor Search on Compile-Time Product Manifolds

arXiv:2610.15215v1 Announce Type: new Abstract: Nearest-neighbor (NN) search underlies countless robotics algorithms, but many state spaces are not Euclidean: orientations live on SO(2) or SO(3) and p

researcharxiv-cs-ro

OccWAM: Occupancy World-Action Models with Joint Scene-to-Ego Flow Matching

arXiv:2610.17688v1 Announce Type: new Abstract: Occupancy world models provide a structured, metric representation of future driving scenes, making them a promising basis for end-to-end autonomous dri

agentsarxiv-cs-ro

On the Optimality of Random Features under General Conditions: Misspecified Cases and Robust Learning

arXiv:2610.18333v1 Announce Type: cross Abstract: Random features provide a standard approach to scaling kernel methods to large datasets by approximating the kernel with a finite-dimensional feature

PING: physics informed graph neural network for advection-diffusion processes with applications to solar power forecasting

arXiv:2610.18280v1 Announce Type: new Abstract: Advection-diffusion plays an essential role in transport phenomena such as atmospheric and cloud dynamics. Improved forecasting of cloud motion, in turn

tutorialsarxiv-cs-lg

Rescuing Points Trapped Inside Incorrect Decision Regions: A target for Evaluating and Improving Forward-Forward Learning

arXiv:2610.16347v1 Announce Type: new Abstract: Forward-Forward learning replaces end-to-end backpropagation with local, layer-wise training objectives. Its variants are evaluated primarily by classif

Retrievable Gradients: Continual Post-Training Without Cumulative Weight Drift

model-releasesarxiv-cs-lg

arXiv:2606.15734v2 Announce Type: replace-cross Abstract: Continual post-training enables models to absorb emerging knowledge after deployment, but repeatedly updating shared parameters can accumulate

Local Ai

Segment Where You Look: Attention as the Interface Between Language Models and Segmenters

arXiv:2610.18729v1 Announce Type: new Abstract: Vision-language models (VLMs) that segment from language must pass the location of the referent to a pixel decoder. The dominant interface compresses it

local-aiarxiv-cs-cv

Startups are built on relationships. That’s why IRL events are a core part of our growth strategy at @lemma_ . We hosted our biggest one yet…

Startups are built on relationships. That’s why IRL events are a core part of our growth strategy at @lemma_ . We hosted our biggest one yet during @SFTechWeek : The Agent Economy Gala. 400+ founders,

agentsjerry-liu--x

Structural Pass Analysis in Football: Learning Pass Archetypes and Tactical Impact from Spatio-Temporal Tracking Data

arXiv:2603.28916v2 Announce Type: replace Abstract: Football action-value approaches estimate scoring, possession, or other downstream outcome value; complementary descriptions can characterise how a

tutorialsarxiv-cs-lg

The AI race: China's open-weight models trail US closed models by just 7 months

Source: whatmodel.sh, an open source AI leaderboard I built (and launched here yesterday). Every point comes from published benchmark results: 22,113 of them across 987 benchmarks, from 1,011 sources,

Using Absorbing Markov Chains + EmbeddingGemma 2 as a Decision Engine: ~2ms inference with 100% GTO Parity on Vegas Blackjack

[UPDATE / RETRACTION: The '100% GTO' claim had a prompt-leakage bug] We patched the repo to pass strictly neutral states, here are the real, honest numbers: • Latency: Still ~2ms (ONNX + Absorbing Mar

VAttnPO: Visual Attention-Guided Policy Optimization

arXiv:2610.16735v1 Announce Type: new Abstract: Multimodal reinforcement learning with verifiable rewards commonly assigns one sequence advantage to an entire response. This outcome-level signal disti

safetyarxiv-cs-cv

What Can Language Models Inherit from Solomonoff Induction? Limits, Attainable Properties, and What Served Conditionals Reveal

model-releasesarxiv-cs-lg

arXiv:2610.14007v1 Announce Type: new Abstract: A familiar line of reasoning runs as follows: language models are flexible approximators trained under a strictly proper loss, so scale brings them clos

Gemini 4 Argon available on Google Cloud, built to help solve your business’ hardest problems

model-releasesgoogle-cloud-ai

Last week we announced that Gemini Enterprise has evolved to make it even simpler to get work done, and introduced the Gemini agent, your new universal agent for work. It's always on and ready to answ

I built a pytorch library of pretrained models for 3D point clouds following timm standards [P]

model-releasesr-machinelearning

https://preview.redd.it/m5e9anluo8vh1.png?width=1080&format=png&auto=webp&s=4c80687e6fe40036843a97ed8975ce46eaab0662 I am excited to share a project I have been working on during the past few years du

Quartermaster 1.7 update now lets you run llama.cpp's new decision models (/v1/systemone) with a playground tab

Quartermaster (my local inference manager: one server that swaps llama.cpp, image, audio and video models in and out of VRAM) can now help you server and manage decision models: Auto-discovered. Drop

Running decision models: Picking quant, VRAM usage

Hi, I see that vllm released d3 (a family of decision models) and llama.cpp already has support for them. I want to try them out. Are decision models sensitive to quantization? I know that for autocom

Sources: Decagon, which offers AI customer service agents and was last valued at $4.5B, hired a bank and is in early talks with buyers, including ServiceNow (Katie Roof/Business Insider)

Katie Roof / Business Insider: Sources: Decagon, which offers AI customer service agents and was last valued at $4.5B, hired a bank and is in early talks with buyers, including ServiceNow — Buzzy AI a

agentstechmeme