Search: “benchmark”

Beyond Static Positional Encoding: Bayesian Time-aware Attention for Non-Stationary Long-term Time Series Forecasting

arXiv:2610.19603v1 Announce Type: new Abstract: Transformers have demonstrated strong performance in long-term time series forecasting (LTSF), yet modeling non-stationary temporal dependencies remains

safetyarxiv-cs-lg

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Model Releases

Beyond Successful Play: Diagnosing Opponent Modeling in Large Language Models

DGX agent

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

model-releasesarxiv-cs-ai

15 Oct 2026

Bridging the Topological Divide: Dual-Branch Graph Distillation with Semantic Priors for Robust Cold-Start Recommendation

arXiv:2610.19578v1 Announce Type: cross Abstract: Graph Collaborative Filtering models have achieved remarkable success in recommendation systems. However, they inherently suffer from a catastrophic r

Hardware

capy-flash: Qwen3.8-Flash-Next (125B MoE) in full NVFP4 on two 16 GB consumer GPUs

First, kudos to Strata. It inspired this project, and while I was building it Strata got much faster and added NVFP4 support, which was my main reason for starting. By then I was too far in to stop, s

hardwarer-localllama

ClawLoop: Self-Improving Agents via Harness-Native Training Loop

arXiv:2610.14118v1 Announce Type: new Abstract: The rapid advancement of Large Language Models (LLMs) has driven their deployment toward general-purpose harness environments, where LLM-based agents op

agentsarxiv-cs-ai

Co-Evolving Acting and Forecasting for Language Agents

arXiv:2610.20597v1 Announce Type: cross Abstract: Training language agents is bottlenecked by the high cost of long-horizon rollouts, yet standard agentic reinforcement learning (RL) learns only from

safetyarxiv-cs-lg

Compare to Correct: Pairwise-Guided Logit Adjustment for LLM Test-Time Scaling

arXiv:2610.18583v1 Announce Type: new Abstract: Sampling-based test-time scaling enhances LLM reasoning by aggregating multiple reasoning paths for the same query. Existing methods use answer frequenc

Applications

Complementary Future Token Pruning for World Action Models

arXiv:2610.19957v1 Announce Type: new Abstract: World action models (WAMs) jointly predict future visual states and robot actions, but processing dense future-frame tokens incurs substantial inference

applicationsarxiv-cs-ro

Consider, Then Choose: Order-Invariant Decisions in System One Models

arXiv:2610.18233v1 Announce Type: new Abstract: System One models answer typed questions in a single forward pass and promise the same answer for the same input. For choice questions, this promise fai

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

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

Correlation-Aware Contextual Bandits with Surrogate Rewards for LLM Routing

arXiv:2607.09015v2 Announce Type: replace Abstract: We study contextual bandit problems with correlated arms and access to surrogate reward signals produced by a machine learning model, motivated by a

researcharxiv-cs-lg

Coupled Harness--Model Evolution for Scientific Equation Discovery

arXiv:2610.17740v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to discover scientific equations from experimental data. Such a discovery system has two parts that m

safetyarxiv-cs-ai

Cross-Scenario Industrial Defect Detection via Domain-Robust Training and Metric-Aligned Selection

arXiv:2610.19540v1 Announce Type: new Abstract: Automated defect detection of industrial boards must remain highly reliable under cross-scenario variations in lighting, surface contaminants, and produ

CSWBench: Evaluating Context-Sensitive Code-Switching in Creative Writing

arXiv:2610.20272v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated multilingual capabilities across diverse language generation and understanding tasks. Yet effective code-

CUSE: Fine-Grained Multimodal Unlearning with Counterfactual Guidance and On-Policy Self-Distillation

arXiv:2610.14763v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) can reproduce sensitive, copyrighted, or unsafe information from their training data. Effective unlearning must

safetyarxiv-cs-ai

DarKnight: Retrieval-Guided Agentic Framework for Breaking Dark Web CAPTCHA Gates

arXiv:2610.19830v1 Announce Type: cross Abstract: Cyber Threat Intelligence (CTI) investigators who monitor dark web marketplaces for leaked credentials and breach listings must pass the diverse CAPTC

DeBoneDiT: Depth-Driven Conditional Bridge Diffusion Transformers for Bone Suppression in Chest X-Ray Images

arXiv:2610.19466v1 Announce Type: new Abstract: Chest X-Ray (CXR) is a primary modality for diagnosing pulmonary diseases, yet the overlap of bony structures often obscures critical radiographic findi

Hardware

DEEPRUBRIC: Evidence-Tree Rubric Supervision for Efficient Reinforcement Learning of Deep Research Agents

arXiv:2606.17029v2 Announce Type: replace Abstract: Deep research agents synthesize long-form reports by searching and reasoning over retrieved evidence. Reinforcement learning with rubric-based rewar

hardwarearxiv-cs-cl

Detection of Potato Plant Leaf Diseases using Convolutional Neural Networks

arXiv:2610.20544v1 Announce Type: new Abstract: Potato is an important food-security crop in Ethiopia, but its production is affected by foliar diseases, particularly early blight and late blight. Thi

DexMimic: A Generalist Dexterous Hand-Object Tracking Policy via Value-Guided Reset Allocation

model-releasesarxiv-cs-ro

arXiv:2610.19089v1 Announce Type: new Abstract: Achieving human-like dexterous manipulation remains a central challenge in robotics. Learning from human hand-object interaction (HOI) datasets offers a

Divergent Paths: Learning an Outcome-Predictive Representation of LLM Agent Trajectories

arXiv:2610.19614v1 Announce Type: cross Abstract: In this work, we reframe agentic trajectories as paths through a shared embedding space of actions and environmental observations. We show that succes

safetyarxiv-cs-cl

Tutorials

Draft-Thinking: Learning Efficient Reasoning in Long Chain-of-Thought LLMs

arXiv:2603.00578v2 Announce Type: replace-cross Abstract: Long chain-of-thought~(CoT) reasoning improves the problem-solving capability of large reasoning models~(LRMs), but often incurs substantial i

tutorialsarxiv-cs-cl

Driving, Fast or Slow? Neuro-Symbolic Guidance for Motion Prediction in Multi-Modal Ground Mobility

arXiv:2606.15251v2 Announce Type: replace-cross Abstract: Accurate and interpretable motion prediction for heterogeneous traffic spaces, including pedestrians, bicycles, cars, and trucks, is essential

Dynamic Conflict Clustering with Lightweight Learning and Strategic Repair for Distributed Constraint Satisfaction

arXiv:2610.15658v1 Announce Type: cross Abstract: Distributed Constraint Satisfaction Problems (DCSPs) model distributed decision-making in multi-agent systems, where agents assign values to local var

agentsarxiv-cs-ai

Edgewise Envelopes Between Balanced Forman and Ollivier-Ricci Curvature

arXiv:2603.13535v5 Announce Type: cross Abstract: Evaluating Ollivier-Ricci (OR) curvature on large-scale graphs is computationally prohibitive due to the necessity of solving an optimal transport pro

researcharxiv-cs-lg

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

Enabling Validation for Robust Few-Shot Recognition

arXiv:2506.04713v4 Announce Type: replace Abstract: A key challenge in Few-Shot Recognition (FSR) is the scarcity of labeled task-specific data for training. Contemporary methods mitigate this challen

researcharxiv-cs-cv

Energy Consumption Analysis of Discrete Diffusion and Autoregressive Language Models

arXiv:2610.19855v1 Announce Type: new Abstract: As Large Language Models (LLMs) continue to scale, their energy consumption during inference has become a critical concern. While Autoregressive (AR) mo

Explorer-Zero: Improving Self-Play for Long-Horizon Tasks with Decomposable Verifiable Rewards

arXiv:2610.19868v1 Announce Type: cross Abstract: Training LLM agents on long-horizon interactive tasks with reinforcement learning typically relies on human-annotated tasks and reliable verification,

agentsarxiv-cs-lg

Eye, Robot: Learning Expressive Gaze Dynamics via a VLM-Guided Transformer-VAE

model-releasesarxiv-cs-ro

arXiv:2610.19635v1 Announce Type: new Abstract: Gaze coordinates attention in human interaction through coupled eye, head, and eyelid motion. A humanoid robot must choose where to look while generatin

Fantastic Metrics and How to Find Them: Meta-Evaluating Metrics for Multi-lingual Style-Personalized Generation

arXiv:2610.19166v1 Announce Type: new Abstract: Meta-evaluation of text generation metrics and LLM-judges is primarily conducted using metric-human correlations. However, prior work has shown that cor

FlowWise: Stateful Fast-Slow Model Serving for Streaming Traffic Intelligence

arXiv:2402.03694v3 Announce Type: replace-cross Abstract: Network traffic analysis in cloud and internet service provider (ISP) networks increasingly relies on machine learning (ML) models, as encrypt

FOLD: Position-Free Far Memory with Local Order for Long-Context Speculative Decoding

arXiv:2610.20392v1 Announce Type: new Abstract: Speculative decoding accelerates LLM generation through lightweight drafting and parallel verification. It is particularly promising for long inputs, wh

Tutorials

ForkGRPO: Efficient Exploration and Fine-Grained Credit Assignment for Diffusion Language Models

arXiv:2610.19408v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) have advanced rapidly, yet strengthening their reasoning through reinforcement learning (RL) remains an open cha

tutorialsarxiv-cs-cl

Fractional is Better: Learnable Derivative Orders in Neural Operator Learning

arXiv:2610.20363v1 Announce Type: new Abstract: Neural operators learn mappings between function spaces, enabling fast surrogate solutions to partial differential equations. Despite remarkable archite

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 Stages to States: Unified Iterative Reasoning for MLLMs

arXiv:2610.15620v1 Announce Type: new Abstract: Multimodal Chain-of-Thought (MCoT) substantially enhances the complex reasoning capabilities of Multimodal Large Language Models (MLLMs) by explicitly m

Frustratingly Easy Majority Voting Using Length Conditioning

arXiv:2610.19890v1 Announce Type: new Abstract: Majority Voting (MV) is a simple and widely used strategy which improves the reasoning accuracy of Large Language Models (LLMs) by allocating additional

safetyarxiv-cs-cl

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

GateSight: Recurrent Memory Anticipates Attention Memory for Query-Agnostic KV Eviction in Hybrid LLMs

arXiv:2610.14754v1 Announce Type: new Abstract: Hybrid language models interleave Gated DeltaNet (GDN) layers, whose recurrent memory has a fixed size, with full-attention layers, whose key-value (KV)

Applications

GBTSVR: Twin Support Vector Regression via Granular Ball Computing

arXiv:2610.20053v1 Announce Type: new Abstract: Regression models used in real-world applications are often challenged by noise, outliers, data heterogeneity, and asymmetric error characteristics, whi

applicationsarxiv-cs-lg

GDBA-Net: A Gated Dual-Branch Adaptation of SAM2 for Robust Cross-Domain Nuclei Segmentation

arXiv:2610.20073v1 Announce Type: new Abstract: Accurate nuclei segmentation underpins quantitative computational pathology, yet remains challenging due to morphological variability, weak boundaries,

Tutorials

GeoThinker-F: Endogenous Predictive World Representations for Fast Spatial Intelligence

arXiv:2610.20592v1 Announce Type: new Abstract: Existing geometry-aware Multimodal Large Language Models (MLLMs) increasingly rely on external 3D encoders to provide structural priors, but executing t

tutorialsarxiv-cs-cv

Graph Coarsening Enables Escaping Local Optima in Compute-Constrained Nonconvex MAX-CUT

arXiv:2610.19043v1 Announce Type: cross Abstract: Because its binary optimization landscape contains exponentially many local optima, MAX-CUT is highly sensitive to initialization. We study Particle P

Graph-free Retrieval with Graph-Modified Embeddings

arXiv:2610.18410v1 Announce Type: cross Abstract: Dense vector retrieval can miss evidence connected through intermediate entities, while direct graph retrieval requires access to the graph at query t

Gray-Box Hallucination Detection in LLMs with Token Identities

arXiv:2610.19996v1 Announce Type: new Abstract: Large language models often produce fluent but factually incorrect output. Gray-box detectors identify such hallucinations from the token-probability st

GroundGUI: GUI Grounding by High-Quality Data and Distillation-to-Reinforcement Learning

arXiv:2610.19100v1 Announce Type: cross Abstract: Constructing robust GUI agents relies on multimodal visual grounding: the ability to precisely map natural language intents to actionable on-screen co

researcharxiv-cs-cl

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