Search: “benchmark”

Has LLM Screening Performance Stalled in Software Engineering Systematic Reviews?

arXiv:2610.10633v1 Announce Type: cross Abstract: Screening in systematic reviews (SRs) is manual and time-consuming. Prior work has explored large language models (LLMs) for automating this step, but

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Model Releases

Heterogeneous-Modal Unsupervised Domain Adaptation via Latent Space Bridging

DGX agent

arXiv:2506.15971v2 Announce Type: replace-cross Abstract: Unsupervised domain adaptation (UDA) effectively bridges the domain gap between a labeled source domain and an unlabeled target domain, but as

model-releasesarxiv-cs-ai

9 Oct 2026

How Should a Prompt Optimizer Spend a Tight Budget? BudgetAPO with Noise-Adaptive Evaluation

arXiv:2610.05671v2 Announce Type: replace Abstract: Automatic prompt optimization (APO) has been widely employed to adapt large language models without updating their weights, yielding promising resul

HRIL: Learning Multimodal Synergy via Higher-Order Tensor Modeling

arXiv:2610.12393v1 Announce Type: new Abstract: Self-supervised multimodal representation learning has achieved remarkable success across diverse domains, yet capturing synergistic information remains

Instance-anchored interaction evidence: Grounding robot plans in human pointing and handling

model-releasesarxiv-cs-ro

arXiv:2610.12157v1 Announce Type: new Abstract: A robot that assists people must often act on what a person has shown rather than said: which of several identical cartons was pointed at, or which box

IntactWorld: Joint World Modeling with Intact Features

arXiv:2610.11174v1 Announce Type: new Abstract: While recent video generation models synthesize highly realistic visuals, they lack a genuine understanding of intrinsic real-world logic. Existing meth

Is In-Domain Training Enough for Fine-Grained Industrial Anomaly Understanding?

arXiv:2610.12310v1 Announce Type: new Abstract: A single multimodal large language model (MLLM) struggles to excel simultaneously at detection, localization, description, and reasoning in multimodal i

Just Weather Scoring: Efficient End-to-end Nowcasting with Distributional Diffusion

arXiv:2610.12189v1 Announce Type: cross Abstract: Generative diffusion models are well-suited for probabilistic precipitation nowcasting, but existing approaches often rely on separately trained compr

KDFP: A first-principles approach to knowledge distillation in large language models

arXiv:2610.10854v1 Announce Type: new Abstract: Knowledge distillation is an established technique for improving the capabilities of small, efficient student models by training them with the represent

LadderEdit: Edit-Level Residual Compression for Memory-Efficient Lifelong Editing of LLMs

model-releasesarxiv-cs-cl

arXiv:2610.11160v1 Announce Type: new Abstract: Lifelong editing of LLMs requires storing thousands of edits after acquisition. A widely used family of approaches attaches one LoRA adapter per edit, w

LAIR-Net: Leaky Alignment-Impulse Residual Networks for Tabular Regression

arXiv:2610.11538v1 Announce Type: cross Abstract: Deep randomized models fix hidden-layer parameters through random initialization and learn only closed-form readouts, typically adding depth by stacki

Language Modeling is Monotone Compression

arXiv:2610.11031v1 Announce Type: cross Abstract: A long-standing hypothesis in artificial intelligence and neuroscience posits that intelligence is closely related to compression: the ability to comp

Tutorials

Lapras: Latent Reasoning for Time Series Language Models

arXiv:2610.11111v1 Announce Type: new Abstract: Time Series Language Models (TSLMs) offer a promising path toward time series understanding by reasoning over temporal signals and producing natural lan

tutorialsarxiv-cs-cl

Latent Core Tokenizer: Compress, but Meaningfully

arXiv:2610.12376v1 Announce Type: new Abstract: Tokenizers are commonly optimized for compression, but a compact vocabulary does not necessarily distribute its capacity evenly across languages. We int

researcharxiv-cs-cl

Applications

Learned Image Compression for Vision-Language-Action Models

arXiv:2606.16253v2 Announce Type: replace-cross Abstract: Vision-language-action (VLA) models increasingly rely on high-frequency multi-camera observations, making visual communication a major bottlen

applicationsarxiv-cs-ai

Learning from Own Solutions: Self-Conditioned Credit Assignment for Reinforcement Learning with Verifiable Rewards

arXiv:2606.18810v2 Announce Type: replace-cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has driven substantial progress in training LLMs for reasoning tasks, but representative

safetyarxiv-cs-ai

Learning infinite context windows in recurrent architectures via spatial neural computing

arXiv:2610.10690v1 Announce Type: new Abstract: Recurrent neural networks (RNNs) offer linear-time scaling with sequence length while requiring only constant memory, yet they struggle to capture long-

researcharxiv-cs-lg

Learning Probabilistic Logic Programs with Functional Gradient Guided Language Models

arXiv:2610.12303v1 Announce Type: new Abstract: Declarative logic programs offer a powerful and interpretable abstraction for encoding relational structure and neurosymbolic reasoning, by expressing d

Learning to Retrieve: Internalizing Memory Retrieval for Video World Models

arXiv:2610.11444v1 Announce Type: new Abstract: Video world models aim to generate explorable, 3D-consistent scene videos conditioned on camera trajectories. Existing approaches often rely on external

Local Timescale Gates for Timescale-Robust Continual Spiking Neural Networks

arXiv:2510.12843v2 Announce Type: replace Abstract: Spiking neural networks (SNNs) promise energy-efficient artificial intelligence on neuromorphic hardware but struggle with tasks requiring both fast

Look Back, Think Ahead: Visual Memory on Demand for Efficient Multimodal Reasoning

arXiv:2610.12060v1 Announce Type: new Abstract: Processing long visual token sequences from high-resolution images makes multi-step reasoning computationally expensive for multimodal Large Language Mo

Lossy Compressive Text Autoencoders

arXiv:2610.10738v1 Announce Type: new Abstract: Our work explores learning a compressed latent representation of text, at the intersection of data compression and representation learning. We propose a

researcharxiv-cs-cl

MAPF-World: Action World Model for Multi-Agent Path Finding

arXiv:2508.12087v3 Announce Type: replace Abstract: Multi-agent path finding (MAPF) studies the problem of planning conflict-free paths for multiple agents from given start locations to designated goa

MAST: Motif-Augmented Diffusion with Search Tree for Spectroscopic Molecular Structure Elucidation

arXiv:2610.12067v1 Announce Type: cross Abstract: Elucidating molecular structures from spectra is a foundational problem in chemical and materials characterization, yet remains challenging due to spe

Measuring and Mitigating Solution Mode Collapse in RLVR

model-releasesarxiv-cs-cl

arXiv:2610.11064v1 Announce Type: cross Abstract: A language model (LM) can usually answer the same question in more than one way, but reinforcement learning with verifiable rewards (RLVR) is indiffer

MemoWM: How World Models Change What Agents Need to Remember

arXiv:2610.10778v1 Announce Type: cross Abstract: Long-term agents face growing storage demands as they accumulate experience. World models capture reusable regularities that can reduce the informatio

MemTrace: State-Consistent Memory for Long-Horizon Coding Agents

arXiv:2610.04838v2 Announce Type: replace Abstract: As coding agents take on long-horizon software evolution tasks spanning multiple files and stages, longer execution trajectories introduce two coupl

MetaEncoder: Exploring the Limit of Bi-Encoders for Multimodal System One Decision Making with Natural Language Interface

arXiv:2610.11316v1 Announce Type: cross Abstract: System One models output constrained decisions and probability distributions rather than free-form text generation. While prevailing paradigms rely on

MiniVer-V: Identifying Minimal Sufficient Evidence for Short Video Verification

model-releasesarxiv-cs-cl

arXiv:2610.11233v1 Announce Type: cross Abstract: A core challenge in short-video fact-checking is identifying which evidence is sufficient to support a verification conclusion. Existing approaches ei

MiniWAM: Learning Compact Future Targets for Efficient World-Action Modeling

arXiv:2610.12194v1 Announce Type: new Abstract: World modeling has emerged as an effective co-training objective for robot policies, giving rise to World Action Models (WAMs) that jointly predict acti

safetyarxiv-cs-ro

MobileWorldBench: Towards Semantic World Modeling For Mobile Agents

arXiv:2512.14014v2 Announce Type: replace Abstract: World models have shown great utility in improving the task performance of embodied agents. While prior work largely focuses on pixel-space world mo

MultiWorldBench: Do Independently Controlled Views Describe One Shared World?

arXiv:2610.11723v1 Announce Type: new Abstract: Multiplayer world models must ensure that independently controlled views remain consistent with one shared and persistent world. We introduce MultiWorld

Natural Language to First-Order Logic LLM-based Autoformalization

arXiv:2610.12030v1 Announce Type: new Abstract: Large Language Models (LLMs) have renewed interest in autoformalization. Yet, when First-Order Logic (FOL) is considered as the target formalism, the fi

researcharxiv-cs-cl

NEMORA: Neural Equivariant Multipole Operators for Long-Range Atomistic Learning

arXiv:2610.10776v1 Announce Type: new Abstract: Equivariant graph neural networks have emerged as foundational architectures for machine-learned interatomic potentials, approaching quantum-chemical ac

researcharxiv-cs-lg

NOMOS: Compiling Written Policies into Statically Verified Tool-Call Gates for LLM Agents

arXiv:2610.11030v1 Announce Type: cross Abstract: Tool-using LLM agents violate the policies they are deployed to enforce, often silently. Prior defenses hand-write rules, query an LLM verifier per ac

Local Ai

Not Every Change Is Necessary: Recoverable Drift in Large Language Model Unlearning

arXiv:2610.11915v1 Announce Type: new Abstract: Machine unlearning in large language models aims to remove unwanted knowledge while preserving the model's remaining capabilities. Although existing met

local-aiarxiv-cs-cl

OmniDex: Scaling Dexterous Hand Grasping to Diverse Cluttered Scenes

arXiv:2610.11194v1 Announce Type: cross Abstract: Dexterous grasping is the foundational primitive in embodied AI, demanding massive data to train robust models. As real-world data collection is expen

On linearity or non-linearity in machine learning for quantum chaotic dynamics

arXiv:2610.10697v1 Announce Type: cross Abstract: Accurately simulating chaotic quantum many-body dynamics remains a major computational challenge for classical methods, due to the rapid buildup and s

On the Clock: Towards Punctual and Productive Time-Budgeted AI Agents

arXiv:2610.10833v1 Announce Type: new Abstract: We study whether small LLM agents can operate effectively under explicit wall-clock time budgets by both respecting the allocated runtime and using avai

On the estimation and validity of AI time horizons---a statistical look at the METR plot

arXiv:2610.12466v1 Announce Type: new Abstract: METR's 50% time horizon measures the human completion time of software tasks that an AI solves with 50% probability, allowing AI capabilities to be expr

Local Ai

Open-Vocabulary Audio-Visual Event Localization via Complex-Valued Fusion

arXiv:2610.11846v1 Announce Type: new Abstract: Open-Vocabulary Audio-Visual Event Localization (OV-AVEL) labels each video segment with an event class, including classes that were never seen during t

local-aiarxiv-cs-cv

Opera: A Verbal Critic Framework for Long-horizon Coding Agents

arXiv:2609.33987v2 Announce Type: replace Abstract: Long-horizon coding agents need timely corrections, yet feedback can be ineffective or even harmful when it misjudges ongoing work or fails to addre

safetyarxiv-cs-cl

OX-NeRF: 3D X-ray Tomography Reconstruction from Sparse Views Using Implicit Neural Representation

arXiv:2610.11547v1 Announce Type: new Abstract: NeRF and Gaussian splatting methods have been successfully applied on X-ray scenes where the views are too sparse for 3D reconstruction via classical me

PAM-ToD: Plug-and-Play Appearance Modeling for Cross-Time-of-Day 3D Gaussian Splatting

arXiv:2610.11572v1 Announce Type: new Abstract: Adapting a pre-trained 3D Gaussian Splatting (3DGS) road scene to a new time of day requires learning appearance changes from a few anchor images while

Local Ai

[Paper] Stepped MoE: Segment-Level Routing with Configurable Inference Complexity

Training large language models (LLMs) is resource-intensive, and adapting them for diverse deployment scenarios with varying computational constraints remains challenging. While elastic architectures

local-air-localllama

PearlVLA: Progressive Embodied Action-Plan Refinement in Latent Space

arXiv:2606.17924v2 Announce Type: replace-cross Abstract: Current Vision-Language-Action (VLA) models face a trade-off between efficient action generation and explicit deliberation. Directly decoding

safetyarxiv-cs-ai

Perceptually Grounded and Semantics-Aware Evaluation for Holistic Co-Speech Gesture Generation

arXiv:2610.11669v1 Announce Type: new Abstract: Holistic and semantics-aware co-speech gesture generation has advanced rapidly, yet evaluation remains behind: objective metrics do not consistently ref

Plan-and-Patch: Diffusion Language Models for Agentic Planning

arXiv:2610.10786v1 Announce Type: new Abstract: Planning is increasingly important for long-horizon agents, where successful execution requires coordinating subgoals, tool use, and intermediate outcom