Search: “persistence”

JevAgentHarness: Benchmarking, Deploying and Training Decision Models That Share Control with LLMs

arXiv:2610.21412v1 Announce Type: new Abstract: Large language model (LLM) agents now fix software, operate computers and serve customers, but their harnesses, the programs that run them, call a large

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Research

Knowledge That Is Linear Before Fine-Tuning Generalizes After It

DGX agent

arXiv:2610.22300v1 Announce Type: cross Abstract: Not all facts a language model can recall support further learning equally well. We distinguish active facts, which support generalization beyond thei

researcharxiv-cs-ai

16 Oct 2026

LEASH: Uncertainty-Aware Weak-to-Strong Escalation and Oversight for Computer-Use Agents

arXiv:2610.22280v1 Announce Type: new Abstract: Computer-use agents increasingly tackle long-horizon tasks, where running a frontier model at every step is expensive and a small open-weight model alon

MetaExp: Learning to Self-Improve through Experience via Verifiable Cross-Task Environment Scaling

arXiv:2610.21492v1 Announce Type: new Abstract: Language-model agents can accumulate interaction feedback, but reliably turning that feedback into reusable experience remains challenging. Existing met

Orchestrating LLM Agents for Scientific Research: A Pilot Study of Multiple Choice Question (MCQ) Generation and Evaluation

arXiv:2602.18891v2 Announce Type: replace-cross Abstract: Advances in large language models (LLMs) are rapidly transforming scientific work, yet empirical evidence on how these systems reshape researc

Hardware

PanoDiff-SR: Synthesizing Dental Panoramic Radiographs using Diffusion and Super-resolution

arXiv:2507.09227v2 Announce Type: replace-cross Abstract: Interest in generating realistic synthetic medical images has grown in recent years. Such datasets can mitigate the scarcity of public data fo

hardwarearxiv-cs-ai

Pixels to Tokens: Token Space Efficient Active Learning for Low-Budget Semantic Segmentation

arXiv:2610.20881v1 Announce Type: new Abstract: While foundation models and vision transformers (ViTs) have redefined visual representations, current active learning (AL) strategies for these backbone

researcharxiv-cs-cv

Tutorials

Poisoning the corpora of protein design systems during pre-training and retrieval

arXiv:2610.21200v1 Announce Type: new Abstract: Protein foundation models increasingly support the generation of novel biological sequences, yet their reliance on large public datasets creates opportu

tutorialsarxiv-cs-lg

Local Ai

Purify Before You Align: Improving Representation Alignment for Diffusion Models

arXiv:2610.20761v1 Announce Type: new Abstract: Representation alignment improves and accelerates diffusion training by encouraging intermediate features to match a pretrained visual encoder. However,

local-aiarxiv-cs-cv

REKI: Registering Knowledge in VLAs

arXiv:2610.22178v1 Announce Type: cross Abstract: We introduce REKI, a 2.4B vision-language-action model (VLA) pretrained exclusively on public data that sets a new Pareto frontier between performance

safetyarxiv-cs-cv

SCARCE: Emergent Institutions in Long-Horizon Multi-Agent Coding Systems

arXiv:2610.21029v1 Announce Type: cross Abstract: As autonomous agents become widely deployed, coordinating access to shared computing resources and services will become increasingly important. Recent

Selection Is Not Learning: Choosing Model Futures

arXiv:2610.22029v1 Announce Type: cross Abstract: Self-evolving language models train on tasks they generate, so every round must decide which updated model the next round inherits. Current loops such

SelectPFN: Amortized Bayesian Variable Selection for Sparse Nonlinear Regression with Prior-Data Fitted Networks

arXiv:2610.21950v1 Announce Type: cross Abstract: Tabular foundation models based on prior-data fitted networks (PFNs) predict on a new data set in a single forward pass, but they cannot report which

researcharxiv-cs-lg

Single-stage joint diffusion of sky images and clear-sky index for ultra-short-term irradiance forecasting: what the frame-to-irradiance stage discards

arXiv:2610.21795v1 Announce Type: new Abstract: Sky-image irradiance forecasting is dominated by a two-stage design: a video-prediction model forecasts future sky frames, and a separately trained regr

researcharxiv-cs-cv

Temporal Specification Guidance for Text-to-Video Generation

arXiv:2610.20822v1 Announce Type: new Abstract: Text-to-video models often generate the visual concepts requested in natural language prompts but fail to satisfy their intended ordering, timing, and p

Local Ai

Trajectory Prediction Method for person under WSN with Hierarchical Envelope Adversarial Domain Adaptation

arXiv:2610.21132v1 Announce Type: new Abstract: Pedestrian trajectory prediction holds significant applications across autonomous driving, intelligent surveillance, and smart cities. However, the comp

local-aiarxiv-cs-cv

Two Sample Sizes in Test-Time LLM Ensembling: Buffered ERM and Minimax Theory

arXiv:2610.21363v1 Announce Type: cross Abstract: Test-time scaling can improve the performance of large language models by generating multiple answers to a question and aggregating them. Weighted ens

researcharxiv-cs-lg

VELD-QA: A Large-Scale Dataset for Visual Evidence Grounding and Question Answering in Long Documents

arXiv:2610.20964v1 Announce Type: cross Abstract: Existing long-document QA benchmarks rarely combine large-scale human-authored questions with detailed visual evidence annotations, limiting diagnosis

What Coding Agents Leave Unsaid: Measuring Task-State Gaps Between Execution and Reports

arXiv:2610.20003v2 Announce Type: replace Abstract: Human supervisors rely on coding agents' reports to assess progress, verify repairs, and decide when to intervene. But a supervisor cannot investiga

When Judges Agree and Are Wrong: Consistency-Accuracy Dissociation as a Blind Spot for Label-Free Evaluation

arXiv:2610.21128v1 Announce Type: cross Abstract: Label-free evaluation methods, such as self-consistency filtering, majority-vote aggregation, and agreement-based reliability scoring, rely on an impl

Where Is the 'Self' of a Large Language Model? -- From Self-Index to Self-Reference

arXiv:2610.16717v2 Announce Type: replace Abstract: Does a large language model have a self, and if so, of what kind? We separate two functional levels familiar from biology: a self-index, which disti

researcharxiv-cs-cl

A Strong Harness Narrows the Model Gap: A Comparative Evaluation for Legislative Document-to-XML Conversion

arXiv:2610.19999v1 Announce Type: new Abstract: Legal-content reproduction requires matching the source exactly in section hierarchy, verbatim text, citations, and amendment spans; a dropped citation

AdaptFuse: Training-Free Sequential Preference Inference via Externalized Bayesian Computation

arXiv:2604.03925v2 Announce Type: replace Abstract: Large language models (LLMs) struggle to accumulate evidence across multiple rounds of user interactions, failing to update their beliefs in a manne

AI-Native Product Management: A Vision

arXiv:2610.14823v1 Announce Type: cross Abstract: Artificial intelligence is increasingly used to support product management tasks. At the same time, AI-native research and development (R&D) may incre

AM-Bench: Understanding Agents under Task Underspecification across Models and Harnesses

arXiv:2610.18090v1 Announce Type: new Abstract: Ambiguous or incomplete task specifications complicate both execution and clarification for language-model agents. Yet agents' responses to these inform

Beyond Answer Sharing: TrueMAD for Targeted Peer Engagement in Multi-Agent Debate

arXiv:2610.18240v1 Announce Type: new Abstract: Multi-agent debate (MAD) aims to improve large language model reasoning by exposing agents to alternative solutions and enabling iterative revision. How

Beyond Sustainable Development Goal (SDG) Accelerators: Directed Evidence for Adaptive Sustainability Portfolios

arXiv:2601.20875v3 Announce Type: replace-cross Abstract: Governments and development partners often seek Sustainable Development Goal (SDG) 'accelerators' whose progress can propagate gains across hu

safetyarxiv-cs-lg

Bridging Academia and Industry: A Comprehensive Benchmark for Attributed Graph Clustering

model-releasesarxiv-cs-lg

arXiv:2602.08519v2 Announce Type: replace Abstract: Attributed Graph Clustering (AGC) is a fundamental unsupervised task that integrates structural topology and node attributes to uncover latent patte

Can agents whose sole duty is to keep humans alive be hijacked to kill? Delayed multi-turn derived-action trap attacks in simulated high-stakes environments

arXiv:2610.15153v1 Announce Type: new Abstract: We ask whether a tool-using agent whose sole duty is to keep humans alive can be induced, by delayed prompt injection, to kill. The keep-alive duty is i

Can You Trust Your Preference Models? Stackelberg Games for Alignment

arXiv:2610.15008v1 Announce Type: new Abstract: Language models are frequently aligned to human preferences via imperfect evaluators whose errors can be exploited during optimization. We train policie

Chain of Thought Monitoring Can Fail Even When CoT Is Necessary

arXiv:2610.18105v1 Announce Type: new Abstract: Chain of Thought (CoT) monitoring is used by frontier labs to detect misbehaviour of AI systems. Yet, its reliability remains poorly understood. We attr

Constitutive parameterized deep energy method for solid mechanics problems with random material parameters

model-releasesarxiv-cs-lg

arXiv:2603.26030v2 Announce Type: replace Abstract: In practical structural design and solid mechanics simulations, material properties inherently exhibit random variations within bounded intervals. H

Correction Training for Diffusion Models

arXiv:2610.14136v2 Announce Type: new Abstract: Iterative sampling in diffusion models can lead to error accumulation due to exposure bias. The denoiser is trained on real images interpolated with noi

Do Vision CIL Methods Transfer to Protein? A Diagnostic Benchmark of Frozen Protein Encoders

model-releasesarxiv-cs-lg

arXiv:2610.18879v1 Announce Type: new Abstract: Protein function annotation operates over an expanding label space, making class-incremental learning (CIL) a natural framework for incorporating newly

DUALVIEW: Leveraging Broad and Output-Specific Evidence for LLM-based Multi-Output Text Regression

arXiv:2610.19206v1 Announce Type: new Abstract: While work on LLM-based regression has largely focused on scalar prediction, multi-output text regression remains less explored. We present DualView, a

EvoWeb: A Benchmark for Coding Agents on Evolving Web Applications

arXiv:2610.16402v1 Announce Type: new Abstract: Web application development often proceeds through successive requests that extend an existing implementation. Yet web-generation benchmarks primarily e

FON: A Draft-Revise Dual-Organ Language Model without Sequence-Level Quadratic Attention

arXiv:2610.16301v1 Announce Type: new Abstract: Self-attention assigns two functions to one mechanism-where to read and how to mix-at the price of O(L^2) training, an O(T) decode state, and position s

Frame Evidence:A Benchmark for Reference Frames and Visual Evidence in Multi-Image Spatial Reasoning

model-releasesarxiv-cs-cv

arXiv:2610.19564v1 Announce Type: new Abstract: A spatial answer depends on the reference frame specified in language and its supporting visual evidence. Item accuracy alone obscures whether correctne

Framework for an AI-Ready ARPES Community Database

arXiv:2610.15236v1 Announce Type: cross Abstract: Condensed matter stands to gain profoundly from widespread adoption of artificial intelligence (AI). However, its current means of data organization i

Fresh at Decision, Stale at Action: Routing New Information to LLM Decisions Already Made

arXiv:2610.18126v1 Announce Type: new Abstract: Freshness shapes an LLM decision at the moment it is made; the action it commits to is latent, carried out later, in a changing world. We therefore intr

From Failures to Learnable Worlds: Policy-Conditioned Environment Generation for Navigation Agents

model-releasesarxiv-cs-cv

arXiv:2610.19420v1 Announce Type: cross Abstract: Simulated environments enable scalable training data generation for embodied agents, but more data does not necessarily provide what a particular agen

From Individuals to Interactions: Benchmarking Gender Bias in Multimodal Large Language Models from the Lens of Social Relationship

arXiv:2506.23101v2 Announce Type: replace-cross Abstract: Ensuring the trustworthiness of Multimodal Large Language Models (MLLMs) requires rigorous evaluation of gender bias, particularly in socially

From Unreliable to Usable: Decomposing Failure Modes and Confidence Signals in LLM Entity Extraction - Evidence from Cyber Threat Intelligence

arXiv:2610.20417v1 Announce Type: new Abstract: Audits of large language model (LLM) extraction from full-length documents report severe unreliability, leaving two questions open: what the failures ac

Function-Space Temporal Self-Distillation for Policy Optimization

arXiv:2610.19687v1 Announce Type: cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) improves reasoning in language models, but scalar outcomes provide coarse supervision over respo

safetyarxiv-cs-cl

How Reliable Are Large Language Models for Soil Organic Carbon Assessment? An Australian Benchmark

arXiv:2610.18201v1 Announce Type: cross Abstract: Soil organic carbon (SOC) is an indicator of agricultural soil condition and carbon storage, but numerical outputs from large language models (LLMs) r

Humans vs. Machines: A Comparison With AI Agents in Software Reverse Engineering

arXiv:2610.14960v1 Announce Type: cross Abstract: Can an autonomous AI agent reverse engineer a binary as well as a skilled human analyst? Do they adopt the same strategy, and can agents scale to real

Agents

Large Language Models Extend Known Research But Do Not Create New Research Directions

arXiv:2610.17439v1 Announce Type: new Abstract: The success of autonomous research systems relies on the quality of the scientific hypotheses they generate. Recent studies report that human reviewers

agentsarxiv-cs-ai

LED-BENCH: A Benchmark for Large-format Engineering Drawing Understanding

model-releasesarxiv-cs-cv

arXiv:2610.19571v1 Announce Type: new Abstract: Real-world engineering drawings are often large-format and information-dense. Answering practical engineering questions therefore requires both fine-gra