Search: “papers”

arXiv:2609.29384v1 Announce Type: cross Abstract: Online handwriting provides a non-invasive and low-cost behavioral biomarker for Alzheimer's disease (AD) detection, as it reflects both cognitive pla

arXiv:2505.15465v2 Announce Type: replace Abstract: This paper introduces Synthetic Enclosed Echoes (SEE), a novel dataset designed to enhance robot perception and 3D reconstruction capabilities in un

The era of omni agents is upon us. This is a great report by the Qwen Team on their omni-modal agents. They present Qwen3.8-Omni-Flash, a natively multimodal model trained for long-horizon agent tasks

arXiv:2609.29396v1 Announce Type: new Abstract: This paper presents and evaluates a Deep Learning-based (DL-based) Signal Quality Assessment (SQA) model to distinguish between clean and noisy ambulato

arXiv:2609.22974v1 Announce Type: new Abstract: In this paper, we investigate the Minimum Obstacle Displacement Planning problem from a robot motion planning perspective. The problem involves determin

arXiv:2211.01566v2 Announce Type: replace-cross Abstract: This paper presents the applications of scientific ray-tracing in modeling and simulating light transport for space-borne image data generatio

arXiv:2609.22774v1 Announce Type: new Abstract: This paper presents our system for Track 2 of the NLPCC 2026 Shared Task 10 on citation-level faithfulness in AI-assisted scientific reporting. Given an

arXiv:2609.24846v1 Announce Type: new Abstract: This paper presents a novel initialization method for range-aided simultaneous localization and mapping (RA-SLAM). The general SLAM problem has a well-k

arXiv:2604.02401v2 Announce Type: replace Abstract: This paper revisits three backup-based safety filters -- Backup Control Barrier Functions (Backup CBF), Model Predictive Shielding (MPS), and gateke

I forked llama.cpp to implement Declarative Attention (arXiv:2609.02737, Google DeepMind and KAIST AI). The model declares in its own output which context chunks it needs <focus magic_chunks='N'>), an

arXiv:2609.19799v1 Announce Type: cross Abstract: LLM-driven evolutionary search finds programs by launching seeds and iterating each one. Papers report a single budget setting, usually one seed run f

arXiv:2609.19644v1 Announce Type: new Abstract: Scientific discovery is defined by the ability to identify the boundaries of existing knowledge and venture into unexplored territory. The ultimate visi

arXiv:2609.18649v1 Announce Type: new Abstract: Warning: This paper contains examples of stereotypes and social bias. LLMs are increasingly used in interactive settings by the general public, making t

arXiv:2609.07595v2 Announce Type: replace-cross Abstract: The same underlying computational problem is solved across unrelated fields under different names: recursive Bayesian state estimation appears

arXiv:2609.14892v1 Announce Type: cross Abstract: In this paper, we derive an explicit solution of the stationary prediction with expert advice PDE for five experts. The formula is given in three regi

arXiv:2609.14803v1 Announce Type: new Abstract: This paper reports experiments across six frontier model types from OpenAI, Anthropic, xAI, and Google DeepMind. Ten independent sessions per model type

arXiv:2609.13466v1 Announce Type: new Abstract: Enterprise AI adoption has reached 78% of organizations globally, yet the infrastructure to govern that adoption has not kept pace. This paper identifie

arXiv:2609.15113v1 Announce Type: cross Abstract: As robotic systems grow more general, legal norms are needed to integrate them into society. This paper extends the isomorphism problem of aligning le

arXiv:2609.12938v1 Announce Type: new Abstract: This research paper contributes to the maritime research community by introducing a comprehensive AIS dataset from Finnish waters, specifically the Balt

arXiv:2609.11559v1 Announce Type: cross Abstract: Large language models (LLMs) and AI-enabled software increasingly participate in systematic-review decisions, yet the information needed to audit thes

arXiv:2609.12328v1 Announce Type: cross Abstract: This paper presents the iterative equivariant filter (IterEqF). The iterative extended Kalman filter (IterEKF) replaces the standard EKF correction st

Hi everybody, we post-trained Qwen 3.8 27B to be more efficient by figuring out which tokens were linked to overthinking and penalizing them without 'attacking' the reasoning length directly then fixe

Anyone else play with vllm-mlx? There was an interesting paper that came out that compared this version of vllm that was originally designed for multi modal inference performance gains, but ended up s

arXiv:2609.06826v1 Announce Type: cross Abstract: This paper examines the theory of Invariant Structural Learning (ISL), which proposes a non-optimization approach to concept formation. Learning is in

arXiv:2609.08740v1 Announce Type: new Abstract: In this paper we derive a Probably Approximately Correct (PAC)-Bayesian error bound for partially observed linear time-invariant (LTI) stochastic dynami

Model available here: Qwen3.8-27B-Uncensored-Genesis-V1-MTP-GGUF This model is a practical realisation of things described in this paper, but adapted by me for machine learning: https://arxiv.org/pdf/

arXiv:2609.05227v1 Announce Type: new Abstract: Recent reports during the AAAI-27 review cycle highlight the risk of reviewers coordinating bids for reciprocal assignment advantage. Prior work treats

arXiv:2609.04651v1 Announce Type: new Abstract: This paper studies adaptive recommendation under intent drift, where feedback from each recommendation outcome can reveal whether the relational evidenc

arXiv:2609.05022v1 Announce Type: new Abstract: This paper presents new tokenization resources for Irish and evaluation measures of alignment with the morphological boundaries of the language. We pres

arXiv:2609.05190v1 Announce Type: new Abstract: In this paper we illustrate a novel architecture generating interpretable behavior and explanations. We refer to this architecture as the Mirror Agent M

A researcher has reported a jailbreak of GPT-6 Astra within a day after release. The attack is described as combination of TIP (Task-in-Prompt) attack from ACL 2025 paper with four other unnamed techn

arXiv:2609.04158v1 Announce Type: cross Abstract: This paper presents an energy-based controller for a multiagent robotic system designed to achieve and maintain a specific formation while moving on a

arXiv:2609.03077v1 Announce Type: new Abstract: This position paper argues that the absence of labels does not imply the absence of human supervision in visual learning, and urges the research communi

arXiv:2609.02981v1 Announce Type: new Abstract: Artificial intelligence is changing the form of applied English materials from fixed paper sequences to adaptive learning systems that can diagnose lear

I want to share a short paper just published exploring a simple but surprisingly effective optimization for sparse MoE reasoning models. The idea: Instead of retraining anything, we just tweak the rou

arXiv:2609.01737v1 Announce Type: new Abstract: Mobile payment applications in Nepal are graphically mediated and largely inaccessible to visually impaired users. This paper presents SpeakPay, a voice

Hey everyone, Wanted to share a short paper we just published exploring a simple but surprisingly effective optimization for sparse MoE reasoning models. The problem: MoE reasoning models (especially

arXiv:2608.30866v1 Announce Type: new Abstract: Building language technologies and conducting NLP research for low-resource languages---particularly when led by native speakers or involving participat

“increasing agent autonomy can gradually make human oversight ineffective by causing approval fatigue, overreliance, loss of situational awareness, and skill degradation.” new paper from @mmitchell_ai

arXiv:2404.12613v4 Announce Type: replace-cross Abstract: In this paper, we study the problem of learning one-dimensional Gaussian mixture models (GMMs) with a specific focus on estimating both the mo

arXiv:2608.31120v1 Announce Type: new Abstract: The motivation for this paper is the investigation of the trade-offs implicit in probabilistic models used in machine learning. Models are often used to

arXiv:2508.14273v3 Announce Type: replace Abstract: As researchers increasingly adopt LLMs as writing assistants, generating high-quality research paper introductions remains both challenging and esse

Loop engineering has emerged as a new skill for AI engineers But there is very little research measuring how effective it is. The best results on full tasks in a new benchmark is ~25%. LoopArena from

Interesting new paper from Alexia Jolicoeur-Martineau (of Tiny Recursive Model fame) and collaborators. They seem to be able to replace quadratic attention with sliding window attention + attention si

// Your LLM judge disagrees with the experts // LLM Judges can be tricky to build. Here is an interesting showcasing why: There propose a reference-full benchmark of hundreds of complete human-to-huma

// Memory is what breaks long-horizon agents // It's undeniable how important memory/recall is for long-horizon tasks. If you are building for long-horizon tasks, this is a great read. (bookmark it) T