Search: “benchmark”

ActICL: Post-Training for Agentic Multimodal In-Context Learning

arXiv:2610.19475v1 Announce Type: cross Abstract: Multimodal in-context learning (ICL) is an important capability of multimodal large language models (MLLMs). Its performance is closely tied to the de

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Model Releases

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

DGX agent

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

model-releasesarxiv-cs-cl

15 Oct 2026

Adaptive Observation Control for Active Visual Recognition

model-releasesarxiv-cs-cv

arXiv:2610.19624v1 Announce Type: new Abstract: Visual recognition models usually process a fixed view under a fixed computation budget, although images often benefit from different scales and amounts

AFCS: Atomic-Fact-Conditioned Synthesis for Factual Knowledge Pretraining

arXiv:2610.20086v1 Announce Type: new Abstract: Synthetic data is increasingly used in language-model pretraining. Existing knowledge-corpus synthesis pipelines, including WRAP and Nemotron-CC, usuall

Alignment Faking - the Train -> Deploy Asymmetry: Through a Game-Theoretic Lens with Bayesian-Stackelberg Equilibria

arXiv:2511.17937v2 Announce Type: replace Abstract: Alignment faking is a form of strategic deception in AI in which models selectively comply with training objectives when they infer that they are in

Any Time, Any Space: A World-State-Centric Framework for Agentic Video Generation

model-releasesarxiv-cs-cv

arXiv:2610.20571v1 Announce Type: new Abstract: Long-form agentic video generation must turn a screenplay into shots that remain spatially and temporally consistent across nonconsecutive requests. Pas

Auditing Future-Memory Use in Point-in-Time Language Agents

arXiv:2610.18602v1 Announce Type: new Abstract: Point-in-time (PIT) agents can recall post-cutoff facts even when their external evidence respects a historical cutoff. We examine whether this access p

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 Equation Search: Conjecture-Guided Discovery with SCOPE and ClosureBench

model-releasesarxiv-cs-lg

arXiv:2610.18938v1 Announce Type: cross Abstract: Most symbolic regression methods optimize candidate equations, but improving an equation's fit does not establish whether its underlying scientific co

Beyond Size: How Gradients Shape Pruning Decisions in Large Language Models

arXiv:2311.04902v3 Announce Type: replace Abstract: Large Language Models (LLMs) with billions of parameters are prime targets for network pruning, which removes some model weights without hurting per

Research

BFHD: Bidirectional Feature Harmonization Decomposition for Heterogeneous Clinical Assessments

arXiv:2610.19352v1 Announce Type: new Abstract: Clinical assessments are often collected using heterogeneous assessment systems across centers and time, leading to records that mix different but relat

researcharxiv-cs-lg

Agents

BluePixel: Toward Native 4K Agentic Image Editing

arXiv:2610.19882v1 Announce Type: new Abstract: Instruction-driven image editing has reached native 4K, yet how such editors are trained remains undisclosed, and pretraining one from scratch is beyond

agentsarxiv-cs-cv

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 LLM Agents Efficiently Identify Appliance Faults? Insights From Diagnosing a Simulated Appliance

arXiv:2610.19291v1 Announce Type: new Abstract: In so-called 'Industry 4.0,' integrated sensors, analytics tools, and other digital technologies supplement industrial workflows, potentiating enhanced

Research

Cascaded Retrieval with Cross-Modal Query Refinement for Efficient Visual Document Search

arXiv:2610.20367v1 Announce Type: new Abstract: Retrieving information from visually rich documents requires matching queries against pages that contain complex evidence in tables, figures, and layout

researcharxiv-cs-cl

Character swap with Minimax in Comfy - Cat Fiction

model-releasesr-stablediffusion

I wanted to see if it was possible to recreate this Genjutsu spam (from Higgsfield) you get all over Tiktok (it is my understanding that it's a combo between Claude and Seedance 2.5) but with Minimax

CockpitHAT: Dependency-Graph-Driven Hierarchical Attribution for Embodied Multi-Agent Cockpits

arXiv:2608.01805v2 Announce Type: replace Abstract: LLM multi-agent systems suffer from Correctness Collapse, where high task-level accuracy conceals severe process-level failures. This is especially

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

Cost-Efficient Privacy Enforcement for Email-Generating LLM Agents under Strategic Information Requests

arXiv:2610.18007v1 Announce Type: cross Abstract: LLM agents now act as delegated communication intermediaries: they read private context, draft messages, and send externally visible emails on behalf

DeepSeek-V4-Flash-0731 on 4x Radeon AI PRO R9700 with affinity: the 'refused' 4-card config works, ~79 tok/s on real cards

model-releasesr-localllama

Follow-up to u/neuromacmd's post from a few weeks back (https://www.reddit.com/r/LocalLLaMA/comments/1wod07t/). The affinity engine (https://codeberg.org/StillDeadcode/affinity) refuses to start on mo

Depth-progressive 3D seismic velocity model building via 2D generative diffusion models

arXiv:2610.14812v1 Announce Type: cross Abstract: Three-dimensional (3D) velocity model building (VMB) remains computationally challenging with conventional approaches and native 3D neural networks, l

Designed to support multiple tasks: - reconstructing particle collisions - identifying particles - flagging unexpected signals - evaluating …

model-releasesmistral-ai--x

Mistral AI introduced a tool aimed at high‑energy physics that can reconstruct particle collisions, identify particles, flag unexpected signals, and evaluate future detector designs. The announcement

Designing Textual Interfaces To Enhance Llm Reasoning On Audio-Visual Question Answering

arXiv:2610.20085v1 Announce Type: cross Abstract: Automatic prompt optimization (APO) has shown strong effectiveness for text-based LLMs and LLM systems, but its application to audio-visual understand

Local Ai

Diff Diffusion: Predicting Edit Paths with Diffusion Models for Efficient Code Editing

arXiv:2610.17831v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) are appealing for code generation because they can update many tokens in parallel, yet many are optimized for

local-aiarxiv-cs-ai

Safety

Does Machine Translation Retain Media Bias?

arXiv:2610.19945v1 Announce Type: new Abstract: Within the most recent two decades, machine translation (MT) has been advanced from a research area to a mature, deployed technology for prose text and

safetyarxiv-cs-cl

DTScribe: Generating Models for Digital Twin Reporting using Local Large Language Models

arXiv:2610.18635v1 Announce Type: cross Abstract: The development of a digital twin brings together many stakeholders and technical components. We have previously investigated the reporting of the con

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

DuplexAct: How Interactive Are Frontier Full-Duplex Spoken Language Models?

arXiv:2610.17738v1 Announce Type: new Abstract: End-to-end (E2E) full-duplex spoken language models (FD-SLMs) enable simutanous listening and speaking continously, requiring models to take appropriate

Empowering Edge Agents: A Systematic Analysis of Edge-Cloud Collaboration in LLM Agent Execution

arXiv:2610.17816v1 Announce Type: new Abstract: Edge-cloud collaboration combines the lower inference overhead and greater data locality of edge-side execution with the stronger capabilities of cloud-

Eval4DiRec: A Unified and Systematic Evaluation Framework for Diffusion-based Recommender Systems

arXiv:2609.34404v2 Announce Type: replace-cross Abstract: Leveraging the strong generative capabilities and stable training dynamics of diffusion models, diffusion-based recommender systems (RSs) have

Fewer Bits, More Tries: Recovering Capability Under Memory Constraints

arXiv:2610.15372v1 Announce Type: new Abstract: Large language models are generally more capable than smaller ones, but their memory requirements can make local deployment difficult. We ask whether pa

Following the Flow the Law Requires: Training Voice Agents to Transfer to Unseen Regulated Procedures in Debt Collection

arXiv:2610.18881v1 Announce Type: new Abstract: Voice agents built on large language models (LLMs) now handle customer calls, but in regulated applications completing the task is not enough: the agent

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

GPT-Rosalind is built to support that work: helping researchers reason across scientific literature and biological data, with scientists bri…

GPT-Rosalind is built to support that work: helping researchers reason across scientific literature and biological data, with scientists bringing the expertise and judgment to evaluate the evidence. E

model-releasesopenai--x

HankelKANet: Lightweight Path Loss Estimation via Physics-Inspired Hankel Convolution

model-releasesarxiv-cs-lg

arXiv:2610.19524v1 Announce Type: new Abstract: Accurate path loss (PL) estimation is essential for wireless network planning and optimization. This paper proposes HankelKANet, a lightweight physics-i

Harmony Harness: Multi-Objective Self-Evolution of Agent Harnesses

arXiv:2610.15150v1 Announce Type: new Abstract: Recent work on self-evolving LLM agents treats the agent harness as an optimization target that can be iteratively improved through execution feedback.

Safety

Holding Agents Accountable with Verifiable Agent Insurance

arXiv:2610.18230v1 Announce Type: cross Abstract: While AI agents are useful for many tasks, they regularly misbehave in destructive ways, such as deleting important data. While prior work has focused

safetyarxiv-cs-ai

Applications

Horizon Scans can be accelerated using novel information retrieval and artificial intelligence tools

arXiv:2504.01627v2 Announce Type: replace-cross Abstract: Introduction: Horizon scanning in healthcare assesses early signals of innovation, crucial for timely adoption. Current horizon scanning faces

applicationsarxiv-cs-ai

How Visko streams real-time world models on Google Cloud TPUs

model-releasesgoogle-cloud-ai

Editor's note: Generative AI startups are moving rapidly beyond static clip generation to build interactive, real-time worlds. In this technical deep dive, we explore how AI startup Visko collaborated

Agents

Interlock: From Local Correctness to Task Completion in Long-Horizon Agents

arXiv:2610.19686v1 Announce Type: new Abstract: Large language model agents increasingly undertake long-horizon tasks in complex environments characterized by fragmented evidence, partially completed

agentsarxiv-cs-cl

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

Research

Knowledge transfer between simple discrete worlds

arXiv:2610.15081v1 Announce Type: new Abstract: Adapting to a new world and reasoning correctly about which outcomes are possible under rules one has not met before is a basic capacity underlying gene

researcharxiv-cs-ai

Tutorials

lambda_0: Scaling Open-World Egocentric Human Data for Humanoid Loco-Manipulation

arXiv:2610.18950v1 Announce Type: cross Abstract: Humanoid loco-manipulation requires coordinated whole-body interaction with the physical world, yet collecting robot demonstrations at scale remains c

tutorialsarxiv-cs-cv

Learnable Hodge-Laplacian Driven Mixture of Experts for Steady-PDE Surrogates on Coarse Unstructured Meshes

model-releasesarxiv-cs-cv

arXiv:2610.20585v1 Announce Type: cross Abstract: Current approaches for steady partial differential equations surrogate models on unstructured meshes apply a single mixing mechanism to the whole solu

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

Lingdan-V2: Large language models for clinically grounded reasoning in traditional Chinese medicine

arXiv:2610.14705v1 Announce Type: cross Abstract: Large language models have advanced medical reasoning, but clinically grounded reasoning in traditional Chinese medicine (TCM) remains challenging bec

Memory Echo in Single-Agent Long-Term Memory: Lifecycle Evaluation and Provenance-Guided Mitigation

arXiv:2610.17763v1 Announce Type: new Abstract: Long-term memory supports agents across sessions. Repeated retrieval and write-back can let one historical claim occupy multiple retrieval positions and

Mitigating Video Hallucinations via Attention-Guided Representation Perturbation

arXiv:2610.19728v1 Announce Type: cross Abstract: Video large language models (Video LLMs) often generate responses unsupported by the input video. Contrastive decoding (CD) can mitigate these halluci