Search: “papers”

How Much Human Label Variation Does Formal Semantic Structure Explain?: Group-Level Effects and Item-Level Ceilings in NLI

arXiv:2607.15870v2 Announce Type: replace Abstract: Human label variation in natural language inference is increasingly treated as signal rather than noise, but how much of it formal semantic structur

researcharxiv-cs-cl

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Agents

How Much of a Harness Does a Strong Agent Need for Autonomous ML Engineering?

DGX agent

arXiv:2609.40303v1 Announce Type: new Abstract: Recent autonomous machine learning engineering (MLE) agents have made significant progress on public leaderboards. Often motivated by progress stagnatio

agentsarxiv-cs-ai

1 Oct 2026

Hardware

HyDRA: A Hybrid Dual-Mode Network for Closed- and Open-Set RFFI with Optimized VMD

arXiv:2507.12133v2 Announce Type: replace Abstract: Device recognition is vital for security in wireless communication systems, particularly for applications like access control. Radio Frequency Finge

hardwarearxiv-cs-lg

Introducing Agent Droplets: everything an agent needs, one price, one bill

model-releasesdigitalocean

Last week we launched DigitalOcean Managed Agents in public preview: a managed runtime, governed access to more than 16,000 tools, serverless inference, and persistent memory and storage, all on one c

Lasting Effects of Abstract Pretraining Beyond Perplexity

arXiv:2609.38764v1 Announce Type: new Abstract: Language models are typically pretrained from random initialization. Recent work challenges this convention, showing that a brief warm-up on abstract, a

Learning-Based Progressive Barrier Control for Robot Manipulators with Initial Errors Outside Prescribed Tracking Bounds

arXiv:2503.14669v2 Announce Type: replace Abstract: Robot manipulators may start a new task with a tracking error larger than the prescribed tolerance. Conventional barrier controllers generally requi

researcharxiv-cs-ro

Learning Normal Diffusion Dynamics for Backdoor Defense in Text-to-Image Models

arXiv:2609.39548v1 Announce Type: cross Abstract: Backdoor attacks pose a serious threat to the secure deployment of text-to-image (T2I) diffusion models. Existing defenses typically detect backdoors

Applications

LogiC-Diff: Embedding Security Properties Into AI-Enabled Cyber-Physical Systems

arXiv:2609.38381v1 Announce Type: cross Abstract: AI-enabled Cyber-Physical Systems (CPS) are highly vulnerable to adversarial and anomalous inputs, where small perturbations can induce cascading erro

applicationsarxiv-cs-ai

Tutorials

Looking Back to Move Forward: Temporal Verification for Generative Robot Policies

arXiv:2609.39038v1 Announce Type: new Abstract: Generative policies have emerged as a promising paradigm for robot learning, combining expressive generative action modeling with scalable imitation lea

tutorialsarxiv-cs-ro

MADBench: Benchmarking the Security of Multi-Agent Debate

arXiv:2609.39146v1 Announce Type: new Abstract: Multi-agent debate (MAD) can improve large language model (LLM) reasoning by allowing multiple agents to exchange and critique their answers to the same

Making Grid Beam Search Less Greedy

arXiv:2609.39368v1 Announce Type: new Abstract: A common formalism for constraining the output of autoregressive text generation models involves lexical constraints, words or phrases which are require

safetyarxiv-cs-cl

Marking Contour Tones in Yoruba

arXiv:2609.38627v1 Announce Type: new Abstract: Yoruba is a tonal language in which contour tones pose persistent orthographic challenges. These are especially notable for personal names and lexical i

researcharxiv-cs-cl

MeshOctave generates meshes via cascading resolution transitions

arXiv:2609.38985v1 Announce Type: new Abstract: Generating compact, artist-style meshes with explicit topology typically relies on autoregressive models which incur prohibitive sequential per-token co

local-aiarxiv-cs-cv

MM-FinEval: A Multi-Task Multimodal Benchmark for Real-World Financial Forecasting

arXiv:2609.38523v1 Announce Type: cross Abstract: Financial forecasting from earnings conference calls requires models to reason over complex corporate disclosures, market expectations, and subtle com

Multidimensional Observer Model and Perceptual Dimensions of Human Image Quality Assessment

arXiv:2609.38487v1 Announce Type: new Abstract: Judging image quality is not only ecologically relevant to everyday human tasks, but also underpins many machine vision tasks such as image generation.

researcharxiv-cs-cv

Non-Invasive Inspection of Water Canals Using Dronar

arXiv:2609.40178v1 Announce Type: new Abstract: Open concrete canals play a vital role in water transportation, serving as primary water infrastructure for millions of people across the Phoenix, Arizo

researcharxiv-cs-ro

Agents

Occlusion-Aware, Quasi-Static, Stability-Oriented Trajectory Planning on Uneven Terrain

arXiv:2609.39105v1 Announce Type: new Abstract: Autonomous navigation in unstructured off-road environments requires reasoning about both vehicle--terrain interaction and environmental unknowns. We pr

agentsarxiv-cs-ro

Offline Guidance, Online Reasoning: Reusing LLM Feedback for Small Language Models

model-releasesarxiv-cs-cl

arXiv:2609.39346v1 Announce Type: new Abstract: Large language models (LLMs) offer strong reasoning capabilities but are often costly to access through commercial APIs, while small language models (SL

On the (Generative) Linear Sketching Problem

arXiv:2603.14474v2 Announce Type: replace Abstract: Sketch techniques have been extensively studied in recent years and are especially well-suited to data streaming scenarios, where the sketch summary

On the (In)effectiveness of AMR Augmentation for Large Language Models

arXiv:2609.40121v1 Announce Type: cross Abstract: While Abstract Meaning Representation (AMR) has historically improved performance on a range of NLP tasks, the benefit---or lack thereof---of AMR augm

Out-of-Distribution Detection using Counterfactual Distance

arXiv:2508.10148v2 Announce Type: replace-cross Abstract: Accurate and explainable out-of-distribution (OOD) detection is required to use machine learning systems safely. Previous work has shown that

PISCO: Precise Video Instance Insertion with Sparse Control

arXiv:2602.08277v3 Announce Type: replace-cross Abstract: The landscape of AI video generation is undergoing a pivotal shift: moving beyond general generation - which relies on exhaustive prompt-engin

Privacy in Personalized AI Is a System Property, Not Just a Model Property

arXiv:2609.38289v1 Announce Type: cross Abstract: In personalized AI applications, such as conversational assistants and recommender systems, users interact not with models in isolation but with broad

Provable Test-Time Scaling for Beam Search in LLM Reasoning

arXiv:2609.38672v1 Announce Type: cross Abstract: Beam-search-based test-time methods provide an effective way to improve large language model (LLM) performance on long-horizon generation by pruning i

Tutorials

Pseudo-Label-Triggered Retraining from Forecast Errors for Online Time Series Forecasting

arXiv:2609.39789v1 Announce Type: cross Abstract: Real-world time series forecasting systems operate under non-stationary data streams, where forecasting performance may degrade over time. Although re

tutorialsarxiv-cs-ai

Representation Risk in Pretrained Image Encoders

model-releasesarxiv-cs-cv

arXiv:2609.35470v1 Announce Type: cross Abstract: Applied researchers increasingly convert images into features with pretrained encoders, then use those features in a downstream prediction model. The

RLTL;DR: Self-Improvement by Internalizing Self-Generated Feedback

The common paradigm of reinforcement learning with verifiable rewards (RLVR) is to let agents make multiple attempts at a task, and optimize towards the successful ones. This becomes problematic in th

safetyapple-ml-research

Robust LassoNet: Enhancing Feature Selection in Neural Networks via Robust Loss Functions

arXiv:2609.38263v1 Announce Type: cross Abstract: Feature selection in neural networks remains a challenging problem, particularly in the presence of noisy or contaminated data. LassoNet is a recent a

Robust Wake-Up Word Detection by Two-stage Multi-resolution Ensembles

arXiv:2310.11379v2 Announce Type: replace-cross Abstract: Voice-based interfaces rely on a wake-up word mechanism to initiate communication with devices. However, achieving a robust, energy-efficient,

local-aiarxiv-cs-cl

SceneJail: Exploiting Video Scenario Context to Jailbreak Multimodal LLMs

arXiv:2609.38899v1 Announce Type: cross Abstract: Video Multimodal Large Language Models (Video-MLLMs) support reasoning over video inputs, yet remain vulnerable to jailbreak attacks that elicit polic

Self-Evolving Algorithm-Design Agents: Escaping In-Context Evolutionary Stagnation via Population-Curated Policy Optimization

arXiv:2609.38757v1 Announce Type: new Abstract: Large language models are increasingly participating in complex real-world tasks in the form of algorithm-design agents, designing and refining algorith

Self-Spec Verifiable Code Generation

arXiv:2609.39568v1 Announce Type: cross Abstract: Large language models (LLMs) may generate unreliable code on corner cases missed by testing, while formal verification can provide machine-checkable g

Sequential Bayesian Evaluation of Large Language Model Behavior

model-releasesarxiv-cs-cl

arXiv:2511.10661v2 Announce Type: replace Abstract: It is increasingly important to evaluate the characteristics of systems based on large language models (LLMs). Evaluations in this context often rel

Simulator-Refined Diffusion for Radio-Frequency Inverse Design

arXiv:2609.38363v1 Announce Type: cross Abstract: Diffusion models have shown potential in inverse design of printed circuit boards (PCBs), enabling the generation of layouts conditioned on target S-p

Hardware

Sparse-WAM: Accelerating World Action Models via Action-Guided Sparse Imagination

arXiv:2609.38984v1 Announce Type: cross Abstract: World-action models (WAMs) leverage pretrained video models to improve generalization in robot control by jointly predicting future visual states and

hardwarearxiv-cs-ai

Applications

Spatio-Temporal Partial Sensing Forecast for Long-term Traffic

arXiv:2408.02689v3 Announce Type: replace-cross Abstract: Traffic forecasting uses recent measurements by sensors installed at chosen locations to forecast the future road traffic. Existing work eithe

applicationsarxiv-cs-ai

Agents

Survival is the Only Reward: Sustainable Self-Training Through Environment-Mediated Selection

arXiv:2601.12310v2 Announce Type: replace Abstract: Self-training systems often degenerate due to the lack of an external criterion for judging data quality, leading to reward hacking and semantic dri

agentsarxiv-cs-ai

Taming Speculative Search for Test-Time Scaling in LLM Serving

arXiv:2609.39334v1 Announce Type: cross Abstract: Test-time scaling has recently emerged as a powerful approach for improving LLM reasoning by allocating additional computation during inference, subst

researcharxiv-cs-cl

Towards Model as a Library: Offline, Community-Sourced AI for Low-Resource African Languages

arXiv:2609.38574v1 Announce Type: new Abstract: Large language models are frequently proposed as a route to AI-powered services for African communities, but they are least reliable exactly where the n

local-aiarxiv-cs-ai

TRACE: Learning to Self-Calibrate Wireless Digital Twins from ISAC Measurements

arXiv:2609.32923v2 Announce Type: replace Abstract: Wireless digital twins (DTs) rely on 3D environment models to predict radio propagation and support wireless-network decisions, yet these models are

Trustworthy Runtime Error Healing in Real-World Repositories: A Benchmark and Guardrail

arXiv:2609.39086v1 Announce Type: cross Abstract: Runtime error healing lets a crashed program continue by generating code that repairs its live runtime state. Recent work shows that LLMs can generate

Unapologetically Distributed: A Call for Decentralized Document Analysis

arXiv:2609.39684v1 Announce Type: new Abstract: Privacy has become an increasingly important concern in the Document Analysis community, to the extent that in many environments such as archives, gover

local-aiarxiv-cs-cv

Uncovering Uncontrolled Repetition through Residual Stream Dynamics

arXiv:2609.38802v1 Announce Type: cross Abstract: Uncontrolled repetition can prolong autoregressive generation in large language models (LLMs) and enable resource consumption attacks. Prior analyses

Unveiling the Value of Motion for Cinematic Camera Trajectories

arXiv:2609.38683v1 Announce Type: cross Abstract: Cinematic camera motion is a fundamental storytelling tool, defined not only by where the camera is positioned in the scene, but also by how it moves

safetyarxiv-cs-ai

Variance-Corrected Multi-Asset Equity Simulation with Hybrid Hidden Markov Marginals

arXiv:2603.10202v3 Announce Type: replace-cross Abstract: Synthetic multi-asset equity data must reproduce each asset's return distribution and its relationship with the market. Reusing a generator fi

Agents

Vision-Language-Action Autonomous Driving Agent with Language-based Memory

arXiv:2609.38641v1 Announce Type: new Abstract: Vision-Language-Action (VLA) foundation models have recently emerged as one of the prevailing solutions for autonomous driving, as they can utilize know

agentsarxiv-cs-cv

We benchmarked 18 RAG pipelines against an agent loop on Google's FRAMES. The best pipeline hit 78.9%. The agent loop hit 92.7%.

model-releasesr-localllama

Hybrid search, reranking, query decomposition, and query expansion are often treated as must-haves for good RAG. We wanted to see how much each actually helped, so we tested them. Same model, same emb

WEIRDO: WEak resIdual Regularized DOob's h-transform diffusion alignment

arXiv:2609.39531v1 Announce Type: cross Abstract: We study the problem of estimating the guidance that steers the distribution learned by a diffusion generative model toward a tilted target q_0 propto

safetyarxiv-cs-lg