Search: “framework”

What Should Robot Policies Learn to Predict? Rethinking Supervision Targets in Vision-Language-Action Learning

arXiv:2610.21915v1 Announce Type: new Abstract: Vision-language-action (VLA) policies are typically trained with action prediction as the primary supervision signal, since robots ultimately execute ac

safetyarxiv-cs-ro

16 Oct 2026

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WorkflowPerturb: Calibrated Stress Tests for Evaluating Multi-Agent Workflow Metrics

DGX agent

arXiv:2602.17990v4 Announce Type: replace Abstract: Multi-agent LLM systems that generate structured workflows from natural-language requests are now deployed in production across cloud automation, De

model-releasesarxiv-cs-ai

16 Oct 2026

X-RIC: An Agentic RAN-Intelligent Controller Benchmark for Enhancing Reinforcement Learning

arXiv:2610.22269v1 Announce Type: new Abstract: The O-RAN ALLIANCE introduces architectural flexibility through disaggregation and AI-driven control. While the RAN Intelligent Controller (RIC) enables

16 Oct 2026

Hardware

ZenFlow: Enabling Stall-Free Offloading for LLM Training

arXiv:2505.12242v4 Announce Type: replace-cross Abstract: Fine-tuning large language models (LLMs) often exceeds GPU memory limits, prompting systems to offload model states to CPU memory. However, ex

hardwarearxiv-cs-lg

16 Oct 2026

A Global View of How LLMs Value Human Time

arXiv:2610.18515v2 Announce Type: cross Abstract: Large language models (LLMs) increasingly act as personal assistants; however, little is known about how they capture national-level preferences on a

ActiveEvidence: Decision-Focused Evidence Graphs with Verifiable Acquisition Gaps

arXiv:2610.20532v1 Announce Type: cross Abstract: A multimodal agent must decide whether visual evidence is worth acquiring, which candidate or resolution to query, and when further interaction can no

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ADAPT: Audio-Depth Action Planning with Transition-Aware Rewards for Lights-Out Industrial Navigation

arXiv:2610.15956v1 Announce Type: new Abstract: Vision-language-action models for embodied navigation typically rely on RGB observations, limiting their applicability in lights-out industrial environm

Agent-Canary-Mas: End-to-End Evaluation of Protocol Risk in Long-Horizon Multi-Agent Systems

arXiv:2610.15529v2 Announce Type: new Abstract: Agent-to-agent protocols allow LLM agents to discover peers, exchange results, and coordinate tool use. A locally successful protocol attack, however, m

AI-Driven, Timing-Aware Power Optimization

arXiv:2610.18890v1 Announce Type: cross Abstract: Post-route power recovery changes cell choices under tightly coupled timing, electrical and physical constraints, and the value of each change depends

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Aligning Faithfulness for Theory-Scale Autoformalization

arXiv:2610.18498v1 Announce Type: cross Abstract: Autoformalization (AF) requires more than compilation: formal statements must preserve the meaning of their informal sources, a property known as fait

Assessing and Refining ChatGPT's Performance in Identifying Targeting and Inappropriate Language: A Comparative Study

arXiv:2505.21710v2 Announce Type: replace Abstract: This study evaluates the effectiveness of ChatGPT, an advanced AI model for natural language processing, in identifying targeting and inappropriate

BANGLAPLAN: A Benchmark for Constraint-Based Planning and Decision-Making in Bangla

arXiv:2610.19704v1 Announce Type: new Abstract: Large language models (LLMs) increasingly help users arrange appointments, plan journeys, and allocate limited resources. These tasks require models to

Beyond Successful Play: Diagnosing Opponent Modeling in Large Language Models

arXiv:2610.17310v1 Announce Type: new Abstract: Language-model agents are expected to adapt to others whose behavior changes through interaction. Yet adaptation may rely on learned behavioral patterns

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

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

Complex materials engineering via Provenance Action Graphs: potential, structure and demonstration

arXiv:2610.18314v1 Announce Type: new Abstract: This work discusses and tests the potential of reaction graphs for material synthesis, in which events consist of reaction steps (actions) and their out

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

Constructed regional photovoltaic generation fields improve ultra-short-term distributed solar forecasting

arXiv:2610.16110v1 Announce Type: new Abstract: Ultra-short-term forecasting of densely distributed photovoltaic (PV) systems remains challenging because external meteorological and satellite products

Correct Choices, Failed Sequences: Choice2Seq Benchmarks Correctness Retention Across Output Interfaces

arXiv:2610.16191v1 Announce Type: new Abstract: A model may select the correct answer yet fail to construct it through a sequence of local decisions. We introduce Choice2Seq, a diagnostic benchmark th

CoverSynth: Coverage-Guided Generation of Retrieval Evaluation Sets

arXiv:2610.15409v1 Announce Type: new Abstract: Enterprise agents need retrieval evaluation sets that expose domain-specific failures and guide developers towards efficient deployment tradeoffs. Neith

Cross-Lingual Transfer of Evil Vectors Is Directionally Asymmetric

arXiv:2610.17880v1 Announce Type: cross Abstract: Persona vectors are linear directions in the residual-stream activations of LLMs that encode behavioral traits and enable fine-grained control over mo

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Decidable Reasoning About Time in Finite-Domain Situation Calculus Theories

arXiv:2402.03164v3 Announce Type: replace Abstract: Representing time is crucial for cyber-physical systems and has been studied extensively in the situation calculus. The most commonly used approach

Decoupled Drift-Diffusion World Models for Consistent Future Frame Prediction

arXiv:2610.19212v1 Announce Type: new Abstract: World models of visual information predict future image frames conditioned on given action sequences. This predicted scene evolution is driven by determ

tutorialsarxiv-cs-cv

Delegating Earth science model calibration to knowledge-guided LLM agents

arXiv:2610.18378v1 Announce Type: new Abstract: Applying process-based Earth science models to new sites and questions often requires expert calibration decisions. Reliable delegation to language-mode

Digital Self-Interference Cancellation for In-Band Full-Duplex Systems Based on Transformer Neural Operators

arXiv:2610.19490v1 Announce Type: cross Abstract: Digital-domain self-interference cancellation is essential in in-band full-duplex radios after passive suppression and analog cancellation. It is part

researcharxiv-cs-lg

DoReMe: Dual optimization of Reconstruction and Motion estimation for self-navigated free-breathing abdominal MRI using Gaussian Splatting

arXiv:2610.19120v1 Announce Type: cross Abstract: Purpose: Free-breathing abdominal MRI is limited by respiratory motion, which introduces image artifacts and k-space inconsistencies. Existing reconst

researcharxiv-cs-cv

DynThinker: Unifying Static 3D and Dynamic 4D Spatial Reasoning

model-releasesarxiv-cs-cv

arXiv:2610.20598v1 Announce Type: new Abstract: Achieving general spatial intelligence requires a unified understanding of both static 3D and dynamic 4D. However, we find that existing models struggle

Engram Injection: A Study of Temporal Validity in Parametric Language-Model Memory

arXiv:2610.15882v1 Announce Type: new Abstract: A stored fact may stop being valid when a user changes a preference or an event replaces an earlier one. We study whether a language model can learn the

tutorialsarxiv-cs-ai

EPOCH: Coverage-Aware Evolution with Experiential Preference Optimization for LLM-based Automated Heuristic Design

arXiv:2610.17379v1 Announce Type: new Abstract: LLM-based automated heuristic design (AHD) discovers heuristics for combinatorial optimization problems (COPs), where an LLM generates candidates in an

Equal-information evaluation of credit assignment in modular financial reinforcement learning

arXiv:2610.14750v1 Announce Type: new Abstract: Credit assignment in modular financial reinforcement learning is difficult to evaluate because an attributed signal may improve a component loss without

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

Executable Prefix Values for Locating Agent Failures

arXiv:2610.17633v1 Announce Type: new Abstract: Work on debugging LLM agents treats the 'first mistake' marked by a human or LLM judge as ground truth for where a trajectory failed. We ask whether suc

From Existing Methods to New Research Ideas: Two Perspectives on Recursive Self-Improvement

arXiv:2610.14625v1 Announce Type: new Abstract: Recursive self-improvement (RSI) offers a route to AI systems that participate in their own continued development. Recent methods allow language agents

From Triage to Impact: A Multi-Hop Reasoning Benchmark for Explainable Persian Hate Speech

arXiv:2610.20370v1 Announce Type: new Abstract: Hate speech has become increasingly prevalent on social media, raising concerns about its detection, interpretation, and moderation. Persian, a relative

Frustratingly Easy Agentic RAG via Portable Skills: A Case Study in Customer Support

arXiv:2610.14428v1 Announce Type: new Abstract: Enterprise workflow automation typically requires retrieving a complete and accurate set of relevant information from large operational document corpora

FUSE: Fairness-aware Update Screening against Byzantine Exploitation in q-Fair Federated Learning

model-releasesarxiv-cs-lg

arXiv:2610.20264v1 Announce Type: new Abstract: Client-level fair federated learning, in the form of q-fair federated learning (q-FFL), agnostic federated learning, or tilted empirical risk minimizati

Google Earth AI Geospatial Reasoning Agent: Capabilities and a Systematic Evaluation

arXiv:2610.15750v1 Announce Type: new Abstract: Google Earth AI is a family of geospatial AI models, together with an agent that orchestrates them. We present this agent, Google Earth AI's Geospatial

GREAT-ESDD: Graph Edge Attention Network for Effectively Steered Delivery Decisions

arXiv:2610.14792v1 Announce Type: new Abstract: Online, same-day delivery requires operators to constantly update their routes, and the routing cost for deliveries increases with the number of custome

tutorialsarxiv-cs-ai

HACHIMI-II: From Role-Play to Learner Behavior Modeling for Faithful Student Simulation

arXiv:2610.19654v1 Announce Type: new Abstract: Simulated students let researchers test tutoring systems and teaching strategies before real learners are available, but only if the simulation reproduc

researcharxiv-cs-cl

Hierarchical Residual Policy Learning for Real-World Mobile Manipulation with Sparse Human Guidance

arXiv:2610.20607v1 Announce Type: cross Abstract: Mobile Manipulation (MoMa) is a cornerstone of autonomous robotic systems, yet real-world fine-tuning remains a formidable challenge because of high-d

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How to Evaluate When You Don't Know How to Evaluate? Choosing Reliable Setups for Base Language Model Benchmarking

arXiv:2610.19185v1 Announce Type: new Abstract: Evaluation of large language models (LLMs) remains largely pre-scientific: it involves many design decisions, with little guidance on how to make them.

Improving Category-Aware Active Domain Adaptation via Uncertainty-Guided Region Coverage

arXiv:2610.19803v1 Announce Type: new Abstract: Active domain adaptation researches focus on alleviating the annotation cost, which comprises source data and target data labelling, as well as enhancin

tutorialsarxiv-cs-cv

Inverse Garment Design with Visual Agents

arXiv:2610.15582v1 Announce Type: new Abstract: We study the problem of inverse garment design, reconstructing simulation-ready 3D outfits with arbitrary layers from a single image, with visual agents

JevGPT: Thinking Fast and Slow in Autonomous Research

arXiv:2610.18272v1 Announce Type: cross Abstract: Autonomous research agents must acquire and reason over evidence within a limited budget. Yet relevant sources can remain uninspected or unused, leavi

Judges Follow the Reference: The Derivation Gap in Verifying Tool-Call Arguments

arXiv:2610.18497v1 Announce Type: new Abstract: Tool-call judges evaluate argument values proposed by LLM agents. We find that they accept a correct value less often when their input holds no referenc

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

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LLMRec: Benchmarking Large Language Models on Recommendation Task

arXiv:2308.12241v2 Announce Type: replace-cross Abstract: Recently, the fast development of Large Language Models (LLMs) such as ChatGPT has significantly advanced NLP tasks by enhancing the capabilit

Logarithmic Scores, Power-Law Discoveries: Disentangling Measurement from Coverage in Agent-Based Evaluation

arXiv:2604.00477v2 Announce Type: replace Abstract: LLM-based agent judges are an emerging approach to evaluating conversational AI, yet a fundamental uncertainty remains: can we trust their assessmen