Search: “context”

Velox: Spatial Memory Makes World Models Efficient

arXiv:2610.22311v1 Announce Type: new Abstract: Video world models turn actions and camera motion into long visual rollouts, making video a natural interface for interactive simulation. Such interacti

safetyarxiv-cs-cv

Volition Elicitation: Operational Semantics for People and Their Machines

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DGX agent

arXiv:2607.14138v2 Announce Type: replace-cross Abstract: The most prevalent distributed systems today include people and their personal machines (smartphones), and computations in them are driven by

agentsarxiv-cs-ai

16 Oct 2026

When Correctness Feedback Erases Evidence: Phase-Separated Completeness Auditing in Verus

arXiv:2610.20676v1 Announce Type: new Abstract: Correctness feedback suppresses the very evidence that specification-completeness auditing is designed to uncover: programs that satisfy a written contr

When is a better LLM worth paying for? Stochastic Optimization with Switching Mixed-Fidelity Oracles

arXiv:2610.21139v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used upstream of decision-making to clean data, detect label errors, and reconstruct missing values. Yet

When Reasoning Is Not Enough: Proactive Inquiry for Cross-Modal Safety in Multimodal Large Language Models

arXiv:2610.22068v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) can act unsafely when individually benign images and texts are interpreted jointly. Beyond implicit reasoning r

WorldCast: Exploring Intelligent Visual Generation in World State Prediction

arXiv:2610.20731v1 Announce Type: cross Abstract: Humans interpret multimodal observations of the world and forecast how it will evolve. Recent multimodal generative systems have demonstrated similar

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

Agent Sociodrama: Social-Dynamics-Guided Persona Recasting for LLM Agent Teams

arXiv:2610.15788v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly deployed as teams, yet they fail in characteristically social ways: information holders stay silent,

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 Black Boxes: Visual Grounding for Text Embeddings

arXiv:2610.18047v1 Announce Type: new Abstract: In this paper, our goal is to represent text embeddings as sketches for three main reasons. First, to visualize text representation and to explore their

Big-Big-SycoBench: A Benchmark to Detect Sycophancy Through Model Responses to Valid vs. Invalid Arguments

arXiv:2610.15634v1 Announce Type: new Abstract: Sycophancy in large language models risks amplifying unsupported claims or beliefs across the knowledge ecosystem as these systems increasingly contribu

CondMSP: Condition-Informed and Resource-Aware Inorganic Materials Synthesis Planning

arXiv:2610.15603v1 Announce Type: new Abstract: Materials synthesis planning (MSP) connects AI-driven materials discovery to experimental realization by proposing precursors, synthesis operations, and

Tutorials

Configuring RAG Systems: What Breaks, Where Originates, and How to Fix

arXiv:2610.18567v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has emerged as a dominant paradigm for improving Large Language Model (LLM) by intertwining it with other component

tutorialsarxiv-cs-ai

Cortex: Measurement-Gated Evolution and Pruning of Coding-Agent Skills and Rules

arXiv:2610.14216v1 Announce Type: cross Abstract: Coding agents such as Claude Code also follow text files that developers write for them: a project file, skills the agent may choose to open, and rule

Do you 'see' what I 'see'? A Multi-panel Visual Question Answer Dataset for Large Language Model Chart Analysis

arXiv:2610.14173v1 Announce Type: cross Abstract: Digital libraries increasingly host scientific publications whose figures encode primary research findings, yet making this visual content searchable,

EGCForest: Structured Agent Memory Organization for Enterprise Group Chats

arXiv:2610.19836v1 Announce Type: new Abstract: Enterprise group chats record project progress, decisions, task ownership, and other organizational information valuable to enterprise agents. Reliable

agentsarxiv-cs-cl

Evaluating LLMs as Agentic Workflow Executors in Real-World Customer Support Skills

arXiv:2610.14346v2 Announce Type: replace Abstract: Enterprise customer-support agents increasingly rely on Large Language Models (LLMs) to execute bounded, tool-using workflows. We study this problem

Fast Diffusion-GAN Model for Generating Symbolic Music with Emotions

arXiv:2310.14040v2 Announce Type: replace-cross Abstract: Diffusion models have shown promising results for a wide range of generative tasks with continuous data, such as image and audio synthesis. Ho

From Efficiency to Sufficiency: The Cost-Aware Measurement Design Framework for Automated Essay Scoring

arXiv:2610.19287v1 Announce Type: cross Abstract: Compute cost in automated essay scoring (AES) is usually treated as a technical efficiency issue rather than a measurement design concern. Yet deploym

Gap Detection: Mitigating Homogenization through Demand and Defensibility

arXiv:2610.20162v1 Announce Type: new Abstract: Language models often produce semantically similar answers to open-ended questions, even when many plausible alternatives exist. Generating useful alter

Glasseek: A Transparent Recipe for Training and Trustworthy Evaluation of DeepSearch Agents

arXiv:2610.16998v1 Announce Type: new Abstract: Deep search enables language agents to solve complex information-seeking tasks through iterative web exploration. However, developing robust open-source

Handoff Curves: Initial Selection, Later Handoff, and Supervision Targets in Multi-turn LLM Routing

arXiv:2610.15993v1 Announce Type: new Abstract: We study how initial model selection, later handoff, and training targets affect success and cost in LLM tasks that span multiple turns. We compare seve

HERO: Harnessing Evidence for Test-time Refinement and Prompt Optimization in Program Generation

arXiv:2610.19184v1 Announce Type: new Abstract: Harness optimization improves LLMs by refining reusable prompts and scaffolding, yet requires further adaptation for program generation tasks such as te

Local Ai

How Inner Optimizers Shape Replica Scaling

arXiv:2610.19064v1 Announce Type: new Abstract: Training large language models (LLMs) across geographically distributed and poorly interconnected compute pools or data centers has become a topic of si

local-aiarxiv-cs-lg

InstructPro2: Natural Language and Biological Grounding Guided De Novo Protein Design

arXiv:2610.19592v1 Announce Type: new Abstract: The ability to generate proteins with desired functions is a central goal of computational biology. Although natural language can express diverse design

researcharxiv-cs-lg

Applications

Label-Centric Knowledge Retrieval for Zero-Shot Text Classification

arXiv:2610.16182v1 Announce Type: new Abstract: Flagship large language models (LLMs) offer rich general knowledge and strong reasoning capabilities, but their high inference cost and latency limit th

applicationsarxiv-cs-ai

Tutorials

Learning How to Remember: Memory Modality Selection for GUI Agents

arXiv:2610.17928v1 Announce Type: new Abstract: Recent advances in vision-language models (VLMs) have substantially improved the capabilities of GUI agents, while memory augmentation has emerged as a

tutorialsarxiv-cs-ai

Learning to GUIDE the Group: Self-Learning LLM Facilitation Across Multi-Party Tasks

arXiv:2610.16231v1 Announce Type: new Abstract: As large language models are increasingly adopted as multi-party communication facilitators, there is a growing demand for agents capable of balancing d

Learning What to Keep: Transfer-Aware Personal Skill Learning from User Feedback

arXiv:2610.19380v1 Announce Type: new Abstract: User feedback enables LLMs to refine reusable personalized skills, but often mixes persistent preferences with request-specific corrections. Indiscrimin

Applications

Learning Who Benefits Most: Multi-Treatment Causal Ranking for Population Health Stratification

arXiv:2610.19782v1 Announce Type: new Abstract: Population health stratification frameworks, such as the Italian DM77, organize patients by clinical need and care pathways but offer limited guidance o

applicationsarxiv-cs-lg

Likelihood Is Not Authorship: Can We Reliably Measure Human Contribution in AI-Assisted Writing?

arXiv:2610.19767v1 Announce Type: new Abstract: AI-text detection generally asks whether a machine wrote a text. As AI becomes an increasingly integral and accepted part of writing, the more relevant

Limitations on Autoregressive Token Generation via Sequential Sampling

arXiv:2610.14615v1 Announce Type: cross Abstract: We study autoregressive token generation through the notion of sequential samplers: A circuit that samples the next symbol only given the previous one

LLM-Based Policy Compliance Verification of Loan Applications

arXiv:2610.20155v1 Announce Type: cross Abstract: Banks rely on extensive internal policy frameworks to ensure that corporate lending decisions comply with regulatory requirements and internal risk st

safetyarxiv-cs-cl

Many Steps into One: Reasoning Contraction and the Limits of Safe Memory Reuse for LLM Agents

arXiv:2610.17544v1 Announce Type: cross Abstract: Thought templates, skill libraries, agent memories and caches turn many reasoning steps into one. We call this reasoning contraction. A contracted mem

MAS-Gate: Unlocking Multi-Agent System Lifecycle via Node-Centric Quantification

arXiv:2610.17613v1 Announce Type: new Abstract: Large language model (LLM)-based multi-agent systems (MAS) can solve complex problems beyond the reach of a single agent by decomposing tasks and coordi

MIND: Lightweight and Effective Memory Injection Defense for LLM Agents via Intent-Aware Information Bottleneck

arXiv:2607.28103v2 Announce Type: replace Abstract: Memory-augmented LLM-based agents are vulnerable to memory injection attacks: Agents may retrieve poisoned memory from attackers, which diverts thei

MultiPartyTurnBench: Benchmarking Floor Control in Multi-Party Spoken Dialogue

arXiv:2610.20172v1 Announce Type: cross Abstract: Full-duplex speech systems must decide when to enter, hold, or relinquish the conversational floor, even as multiple speakers overlap or backchannel w

New Model, Old Habits: Behavior Transfer under Model Swapping in Multi-Session LLM Agents

model-releasesarxiv-cs-lg

arXiv:2610.19712v1 Announce Type: new Abstract: Multi-session agents can switch between LLMs to balance performance and inference cost. Such switches require transferring a history for continuity, yet

North or South? Diagnosing LLMs' Understanding of North Korean Language, Society, and Knowledge

arXiv:2610.15282v1 Announce Type: cross Abstract: Large Language Models (LLMs) have made substantial progress in multilingual question answering, yet their ability to understand low-resource socioling

Open-MMUnlearning: Unifying Methods and Evaluation for MLLM Unlearning

arXiv:2610.10358v2 Announce Type: replace Abstract: As multimodal large language models (MLLMs) become more capable and widely deployed, concerns about privacy and safety have become increasingly pres

PA1-OPD: One-Step Prefix-Augmented On-Policy Distillation for Language Model Pretraining

arXiv:2610.19601v1 Announce Type: new Abstract: Knowledge distillation (KD) improves language-model pretraining by matching teacher distributions at corpus prefixes, but provides no direct supervision

safetyarxiv-cs-cl

Local Ai

PairIT: Autoregressive Transformers for Low-Data Molecule Optimization

arXiv:2610.19123v1 Announce Type: new Abstract: Generating novel molecules with desired properties is a central challenge in drug discovery. Although foundational work focused on de novo generation, p

local-aiarxiv-cs-lg

pi-CoT: Prolog-Initialized Chain-of-Thought Prompting for Multi-Hop Question-Answering

arXiv:2506.20642v3 Announce Type: replace Abstract: Chain-of-Thought (CoT) prompting significantly enhances large language models' (LLMs) problem-solving capabilities, but still struggles with complex

PN-Mix: Pair-Norm Guided Mixed-Precision Key Cache Quantization for Efficient Long-Output LLM Inference

arXiv:2610.19605v1 Announce Type: cross Abstract: Long-output inference in large language models suffers from severe KV cache memory and bandwidth bottlenecks. While KV cache quantization alleviates t

Queue-Aware Token Communications: Bridging AI Representation and Wireless Service

arXiv:2610.16730v1 Announce Type: new Abstract: The rapid advancement of foundation models and edge intelligence is transforming wireless networks from data-oriented communication systems into artific

Reclaiming Low-Quality Instruction Data with Rule-Guided LLM Reconstruction

arXiv:2510.23160v2 Announce Type: replace Abstract: Data selection for supervised fine-tuning (SFT) often discards low-scoring instruction examples that may retain useful supervision. We propose a rul

ReCreate: Reasoning and Creating Domain Agents Driven by Experience

arXiv:2601.11100v3 Announce Type: replace Abstract: Large Language Model (LLM) agents are reshaping the industrial landscape. However, most practical agents still rely on human-designed scaffolds, mak

RetailAgent: Structured Adverse Timing in Self-Conditioned Multimodal LLM Trading Agents

arXiv:2608.28399v2 Announce Type: replace Abstract: In financial markets, a sequential policy that reacts systematically to price movements may become predictable to other market participants. This pa