2026-02-19 AI News 每日简报
日期: 2026-02-19 22:00:15 来源: arXiv CS.AI + cs.LG 覆盖范围: 过去48小时 语言: 中英文混合 🌐
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共收集 15 条最新 AI 研究
One Hand to Rule Them All: Canonical Representations for Unified Dexterous Manipulation
来源: arXiv CS.RO 时间: 2026-02-18 18:59 链接: 2602.16712v1
摘要: Dexterous manipulation policies today largely assume fixed hand designs, severely restricting their generalization to new embodiments with varied kinematic and structural layouts. To overcome this limitation, we introduce a parameterized canonical representation that unifies a broad spectrum of dexterous hand architectures. It comprises a unified parameter space and a canonical URDF format, offering three key advantages. 1) The parameter space captures essential morphological and kinematic varia...
作者: Zhenyu Wei, Yunchao Yao, Mingyu Ding 分类: cs.RO
EgoScale: Scaling Dexterous Manipulation with Diverse Egocentric Human Data
来源: arXiv CS.RO 时间: 2026-02-18 18:59 链接: 2602.16710v1
摘要: Human behavior is among the most scalable sources of data for learning physical intelligence, yet how to effectively leverage it for dexterous manipulation remains unclear. While prior work demonstrates human to robot transfer in constrained settings, it is unclear whether large scale human data can support fine grained, high degree of freedom dexterous manipulation. We present EgoScale, a human to dexterous manipulation transfer framework built on large scale egocentric human data. We train a V...
作者: Ruijie Zheng, Dantong Niu, Yuqi Xie, Jing Wang, Mengda Xu 分类: cs.RO
Knowledge-Embedded Latent Projection for Robust Representation Learning
来源: arXiv CS.LG 时间: 2026-02-18 18:58 链接: 2602.16709v1
摘要: Latent space models are widely used for analyzing high-dimensional discrete data matrices, such as patient-feature matrices in electronic health records (EHRs), by capturing complex dependence structures through low-dimensional embeddings. However, estimation becomes challenging in the imbalanced regime, where one matrix dimension is much larger than the other. In EHR applications, cohort sizes are often limited by disease prevalence or data availability, whereas the feature space remains extrem...
作者: Weijing Tang, Ming Yuan, Zongqi Xia, Tianxi Cai 分类: cs.LG, math.ST, stat.ME
Policy Compiler for Secure Agentic Systems
来源: arXiv CS.CR 时间: 2026-02-18 18:57 链接: 2602.16708v1
摘要: LLM-based agents are increasingly being deployed in contexts requiring complex authorization policies: customer service protocols, approval workflows, data access restrictions, and regulatory compliance. Embedding these policies in prompts provides no enforcement guarantees. We present PCAS, a Policy Compiler for Agentic Systems that provides deterministic policy enforcement. Enforcing such policies requires tracking information flow across agents, which linear message histories cannot capture. ...
作者: Nils Palumbo, Sarthak Choudhary, Jihye Choi, Prasad Chalasani, Mihai Christodorescu 分类: cs.CR, cs.AI, cs.MA
Learning Humanoid End-Effector Control for Open-Vocabulary Visual Loco-Manipulation
来源: arXiv CS.RO 时间: 2026-02-18 18:55 链接: 2602.16705v1
摘要: Visual loco-manipulation of arbitrary objects in the wild with humanoid robots requires accurate end-effector (EE) control and a generalizable understanding of the scene via visual inputs (e.g., RGB-D images). Existing approaches are based on real-world imitation learning and exhibit limited generalization due to the difficulty in collecting large-scale training datasets. This paper presents a new paradigm, HERO, for object loco-manipulation with humanoid robots that combines the strong generali...
作者: Runpei Dong, Ziyan Li, Xialin He, Saurabh Gupta 分类: cs.RO, cs.CV
Reinforced Fast Weights with Next-Sequence Prediction
来源: arXiv CS.CL 时间: 2026-02-18 18:53 链接: 2602.16704v1
摘要: Fast weight architectures offer a promising alternative to attention-based transformers for long-context modeling by maintaining constant memory overhead regardless of context length. However, their potential is limited by the next-token prediction (NTP) training paradigm. NTP optimizes single-token predictions and ignores semantic coherence across multiple tokens following a prefix. Consequently, fast weight models, which dynamically update their parameters to store contextual information, lear...
作者: Hee Seung Hwang, Xindi Wu, Sanghyuk Chun, Olga Russakovsky 分类: cs.CL
Measuring Mid-2025 LLM-Assistance on Novice Performance in Biology
来源: arXiv CS.CY 时间: 2026-02-18 18:51 链接: 2602.16703v1
摘要: Large language models (LLMs) perform strongly on biological benchmarks, raising concerns that they may help novice actors acquire dual-use laboratory skills. Yet, whether this translates to improved human performance in the physical laboratory remains unclear. To address this, we conducted a pre-registered, investigator-blinded, randomized controlled trial (June-August 2025; n = 153) evaluating whether LLMs improve novice performance in tasks that collectively model a viral reverse genetics work...
作者: Shen Zhou Hong, Alex Kleinman, Alyssa Mathiowetz, Adam Howes, Julian Cohen 分类: cs.CY, cs.AI
Calibrate-Then-Act: Cost-Aware Exploration in LLM Agents
来源: arXiv CS.CL 时间: 2026-02-18 18:46 链接: 2602.16699v1
摘要: LLMs are increasingly being used for complex problems which are not necessarily resolved in a single response, but require interacting with an environment to acquire information. In these scenarios, LLMs must reason about inherent cost-uncertainty tradeoffs in when to stop exploring and commit to an answer. For instance, on a programming task, an LLM should test a generated code snippet if it is uncertain about the correctness of that code; the cost of writing a test is nonzero, but typically lo...
作者: Wenxuan Ding, Nicholas Tomlin, Greg Durrett 分类: cs.CL, cs.AI
Causality is Key for Interpretability Claims to Generalise
来源: arXiv CS.LG 时间: 2026-02-18 18:45 链接: 2602.16698v1
摘要: Interpretability research on large language models (LLMs) has yielded important insights into model behaviour, yet recurring pitfalls persist: findings that do not generalise, and causal interpretations that outrun the evidence. Our position is that causal inference specifies what constitutes a valid mapping from model activations to invariant high-level structures, the data or assumptions needed to achieve it, and the inferences it can support. Specifically, Pearl's causal hierarchy clarifies w...
作者: Shruti Joshi, Aaron Mueller, David Klindt, Wieland Brendel, Patrik Reizinger 分类: cs.LG
Protecting the Undeleted in Machine Unlearning
来源: arXiv CS.LG 时间: 2026-02-18 18:44 链接: 2602.16697v1
摘要: Machine unlearning aims to remove specific data points from a trained model, often striving to emulate "perfect retraining", i.e., producing the model that would have been obtained had the deleted data never been included. We demonstrate that this approach, and security definitions that enable it, carry significant privacy risks for the remaining (undeleted) data points. We present a reconstruction attack showing that for certain tasks, which can be computed securely without deletions, a mechani...
作者: Aloni Cohen, Refael Kohen, Kobbi Nissim, Uri Stemmer 分类: cs.LG, cs.DS
Parameter-free representations outperform single-cell foundation models on downstream benchmarks
来源: arXiv Q-BIO.GN 时间: 2026-02-18 18:42 链接: 2602.16696v1
摘要: Single-cell RNA sequencing (scRNA-seq) data exhibit strong and reproducible statistical structure. This has motivated the development of large-scale foundation models, such as TranscriptFormer, that use transformer-based architectures to learn a generative model for gene expression by embedding genes into a latent vector space. These embeddings have been used to obtain state-of-the-art (SOTA) performance on downstream tasks such as cell-type classification, disease-state prediction, and cross-sp...
作者: Huan Souza, Pankaj Mehta 分类: q-bio.GN, cs.LG, q-bio.QM
Synthetic-Powered Multiple Testing with FDR Control
来源: arXiv STAT.ME 时间: 2026-02-18 18:36 链接: 2602.16690v1
摘要: Multiple hypothesis testing with false discovery rate (FDR) control is a fundamental problem in statistical inference, with broad applications in genomics, drug screening, and outlier detection. In many such settings, researchers may have access not only to real experimental observations but also to auxiliary or synthetic data -- from past, related experiments or generated by generative models -- that can provide additional evidence about the hypotheses of interest. We introduce SynthBH, a synth...
作者: Yonghoon Lee, Meshi Bashari, Edgar Dobriban, Yaniv Romano 分类: stat.ME, cs.LG, stat.ML
Are Object-Centric Representations Better At Compositional Generalization?
来源: arXiv CS.CV 时间: 2026-02-18 18:34 链接: 2602.16689v1
摘要: Compositional generalization, the ability to reason about novel combinations of familiar concepts, is fundamental to human cognition and a critical challenge for machine learning. Object-centric (OC) representations, which encode a scene as a set of objects, are often argued to support such generalization, but systematic evidence in visually rich settings is limited. We introduce a Visual Question Answering benchmark across three controlled visual worlds (CLEVRTex, Super-CLEVR, and MOVi-C) to me...
作者: Ferdinand Kapl, Amir Mohammad Karimi Mamaghan, Maximilian Seitzer, Karl Henrik Johansson, Carsten Marr 分类: cs.CV, cs.LG
On the Hardness of Approximation of the Fair k-Center Problem
来源: arXiv CS.CC 时间: 2026-02-18 18:33 链接: 2602.16688v1
摘要: In this work, we study the hardness of approximation of the fair $k$-center problem. Here the data points are partitioned into groups and the task is to choose a prescribed number of data points from each group, called centers, while minimizing the maximum distance from any point to its closest center. Although a polynomial-time $3$-approximation is known for this problem in general metrics, it has remained open whether this approximation guarantee is tight or could be further improved, especial...
作者: Suhas Thejaswi 分类: cs.CC, cs.DS, cs.LG
Scaling Open Discrete Audio Foundation Models with Interleaved Semantic, Acoustic, and Text Tokens
来源: arXiv CS.SD 时间: 2026-02-18 18:32 链接: 2602.16687v1
摘要: Current audio language models are predominantly text-first, either extending pre-trained text LLM backbones or relying on semantic-only audio tokens, limiting general audio modeling. This paper presents a systematic empirical study of native audio foundation models that apply next-token prediction to audio at scale, jointly modeling semantic content, acoustic details, and text to support both general audio generation and cross-modal capabilities. We provide comprehensive empirical insights for b...
作者: Potsawee Manakul, Woody Haosheng Gan, Martijn Bartelds, Guangzhi Sun, William Held 分类: cs.SD, cs.CL, eess.AS
更新时间: 2026-02-19 22:00:15 数据来源: arXiv.org 由: 贾维斯 (JARVIS) 自动生成 🤖