Search: “benchmark”

Spend Bytes on Breadth: Precision-Count Trade-offs for Decode-Time KV Compression in Long Chain-of-Thought Reasoning

arXiv:2610.05685v2 Announce Type: replace Abstract: Reasoning models write most of their KV cache while decoding long chains of thought (CoT), so the cache has to be compressed online under a fixed me

researcharxiv-cs-cl

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Agents

SPIN: Shadow Predictive Indexer for Sparse Attention

DGX agent

arXiv:2610.09025v1 Announce Type: new Abstract: Indexer-based sparse attention reduces the cost of core attention by passing only a fixed, small number of important tokens to it. However, the indexer

agentsarxiv-cs-lg

8 Oct 2026

STRIKE: Learning Visual State Transitions for Physical World Modeling

arXiv:2610.09514v1 Announce Type: new Abstract: Physical world modeling requires predicting how interactions change a scene, not merely generating coherent motion. We propose STRIKE, a framework that

Task-Oriented Key-Layer KV Communication for Efficient Latent Multi-Agent Collaboration

arXiv:2610.08820v1 Announce Type: new Abstract: Large language model-based multi-agent systems improve complex problem solving through collaboration, while latent communication directly transmits mode

agentsarxiv-cs-lg

The Best Optimizer Depends on Batch Size

model-releasesarxiv-cs-lg

arXiv:2610.08975v1 Announce Type: new Abstract: A plethora of new adaptive optimizers are designed to efficiently estimate and use minibatch gradient statistics to shape parameter updates, but they ar

The Long Road to the Same Answer: Cognitive Bias Under Escalating Reasoning Budgets in Large Language Models

model-releasesarxiv-cs-cl

arXiv:2610.10049v1 Announce Type: new Abstract: Reasoning models allocate extra computation at inference time and present their answers as the product of deliberate thought. If this deliberation works

The Symbol of the Surrogate: Measuring Numerical Provenance in Neural PDE Solvers

arXiv:2610.09255v1 Announce Type: new Abstract: Neural PDE surrogates are trained on numerical solver outputs that contain both physical evolution and solver-specific discretization errors. Because su

safetyarxiv-cs-lg

TopoCurve: Geometry-Aware Topology Reasoning via Bezier Curves in Autonomous Driving

arXiv:2610.09118v1 Announce Type: new Abstract: Topology reasoning jointly detects 3D lanes and traffic elements from multi-view images and infers their structural connectivity. Current methods model

TouchScale: 500 Hours of Human Vision and Touch for Visual-Tactile Learning

arXiv:2610.10288v1 Announce Type: new Abstract: Large-scale egocentric human interaction data is becoming an important source of physical supervision for embodied learning, yet video alone leaves the

safetyarxiv-cs-cv

Towards AI-Generated Music Plagiarism Detection as a Version Identification Problem

model-releasesarxiv-cs-lg

arXiv:2610.09075v1 Announce Type: cross Abstract: The rapid expansion of text-to-music generative models challenges traditional paradigms of music creation and intellectual property. Plagiarism in thi

Towards Calibrated Probabilistic Forecasts for Events of Interest via Outcome-Conditional Recalibration

arXiv:2610.10076v1 Announce Type: cross Abstract: Calibration is an essential requirement for probabilistic predictions to be useful for decision making. While state-of-the-art prediction methods ofte

researcharxiv-cs-lg

TR-PTQ: High-Accuracy Integer-Only Transformer Post Training Quantization via Taylor Region Reformulation

arXiv:2610.09969v1 Announce Type: new Abstract: Post-training quantization (PTQ) enables efficient deployment, yet transformer architectures remain challenging to quantize due to nonlinear layers. Whi

researcharxiv-cs-lg

Local Ai

Training Parallel Speculative Draft Models by Directly Minimizing Expected Decoding Rounds

arXiv:2610.10411v1 Announce Type: cross Abstract: Speculative decoding accelerates large language model inference by using a low-cost draft model to propose tokens that the full-size target model veri

local-aiarxiv-cs-cl

Tutorials

Trajectory Planning without Trajectory Data: A Manifold-Guided Approach

arXiv:2610.08863v1 Announce Type: new Abstract: A common way for trajectory planning is to leverage generative models trained on large collections of expert trajectories. At inference time, the model

tutorialsarxiv-cs-ro

U-Space: Uncovering When and Why Uncertainty Arises in Language Models

arXiv:2610.09087v1 Announce Type: new Abstract: Large language models are informing decisions with ever-higher stakes. As the consequences of their errors grow, a central question becomes harder to ig

researcharxiv-cs-cl

Understanding and Mitigating Token-Pruning-Induced Vulnerabilities in VLMs

arXiv:2610.09703v1 Announce Type: cross Abstract: Token-Pruning accelerates Vision-Language Models by removing redundant visual tokens, yet its safety implications remain underexplored. In this work,

safetyarxiv-cs-lg

Applications

Vectorizing the Trie: Efficient Constrained Decoding for LLM-based Generative Retrieval on Accelerators

arXiv:2602.22647v3 Announce Type: replace-cross Abstract: Generative retrieval has emerged as a powerful paradigm for LLM-based recommendation. However, industrial recommender systems often benefit fr

applicationsarxiv-cs-cl

Tutorials

Video-Conditioned Generative Joint 2D-3D Hand Motion Recovery

arXiv:2610.10512v1 Announce Type: new Abstract: Recovering faithful 3D hand motion from video remains challenging due to frequent occlusions and incomplete visual observations, which make frame-wise p

tutorialsarxiv-cs-cv

VideoEvolve: Co-Evolving Memory and Retrieval for Long Video Understanding

arXiv:2610.10183v1 Announce Type: new Abstract: Long video understanding increasingly relies on external memory to organize massive visual streams into compact representations. However, most memory-ba

agentsarxiv-cs-cv

Visual Evidence Under Cross-Examination: Evaluating and Controlling Decision-Level Evidence Use in Vision-Language Models

arXiv:2610.09550v1 Announce Type: new Abstract: Vision-language models increasingly reason through crops, regions, and tool-produced observations. Yet an observation can influence the answer without b

VolCo: Volumetric Contact for High-Fidelity Human Grasp Generation

arXiv:2610.10197v1 Announce Type: new Abstract: Accurate contact modeling is fundamental to understanding hand-object interaction, yet existing contact representations are typically restricted to obje

Hardware

YANchor-4B: Effective Long-Horizon Reasoning in O(N) Time with O(1) Memory

arXiv:2610.10118v1 Announce Type: cross Abstract: Long-horizon reasoning demands access to earlier information at a manageable generation cost. Full-history attention incurs growing storage and comput

hardwarearxiv-cs-cl

Zero-Shot Brain MRI Inpainting with 2.5D Unconditional Flow Priors

arXiv:2610.08983v1 Announce Type: new Abstract: Generative inpainting of brain MRI volumes is essential for synthesizing healthy tissue in pathological regions, improving the accuracy and reliability

2D Spatial Reasoning with Adaptive Neural Cellular Automata

arXiv:2610.08518v1 Announce Type: new Abstract: Many modern learning approaches are still struggling with spatial reasoning tasks, i.e. they lack the ability to utilize geometric information of percei

3D-DefectBench: A Controlled Factorial Study of Vision-Language Model Evaluation Pipelines for Fine-Grained 3D Generation Defects

arXiv:2607.10826v2 Announce Type: replace-cross Abstract: Automated evaluation is essential for scaling generative 3D systems, where exhaustive human review is costly and slow. Yet the reliability of

4D-HOF: Hand-Object Flow Matching for Feed-Forward 4D Interaction Reconstruction

arXiv:2610.08782v1 Announce Type: cross Abstract: Existing methods for 4D hand-object reconstruction often rely on costly per-sequence optimization, while generative approaches typically synthesize in

ActTune: Action-Aware Precision and GPU Operating-Point Adaptation for Energy-Efficient Vision-Language-Action Inference

model-releasesarxiv-cs-ro

arXiv:2610.08444v1 Announce Type: new Abstract: Vision-language-action (VLA) policies repeatedly invoke inference to control robots, making graphics processing unit (GPU) energy a recurring cost of ta

Agent in a Bottle: Can LLM Agents Turn Their Capabilities Into Cheap, Scalable Artifacts?

arXiv:2610.08775v1 Announce Type: new Abstract: Large language models (LLMs) can solve many narrow tasks, but querying them separately for millions of related instances can be prohibitively expensive.

Agentic AI with Structured CoT for Enhancing AI's Spatial Intelligence: Visualization and Reasoning of Rotation

arXiv:2610.04188v2 Announce Type: replace Abstract: Recent studies show that artificial intelligence (AI) with language and vision capabilities still experiences limitations in spatial reasoning. In t

Agentic AutoRAG: RAG Pipeline Optimization through Reasoning-Driven Agents

arXiv:2610.08452v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) is a widely used approach for grounding large language models (LLMs) in external knowledge. However, configuring a

agentsarxiv-cs-cl

APEX: Active Protection at Execution Boundaries for LLM Agents

arXiv:2610.06966v1 Announce Type: cross Abstract: Indirect prompt injection (IPI) hides adversarial instructions in content that large language model (LLM) agents read at runtime. As agents compose he

AttSVD:Prompt-Adaptive Low-Rank KV Cache Compression via Attention-Guided SVD

arXiv:2610.06927v1 Announce Type: cross Abstract: The key-value (KV) cache of autoregressive transformers grows linearly with context length and dominates memory at long context. Most training-free re

Behavioral Cloning Mystery

model-releasesarxiv-cs-lg

arXiv:2610.07056v1 Announce Type: cross Abstract: Behavioral cloning (BC), despite its simplicity, exhibits many counterintuitive phenomena in the real world. For example, the performance of BC often

Beyond Scalar IoU: Structured Verification from Rollout Groups for Video Temporal Grounding

arXiv:2610.07601v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) provides a natural framework for adapting pretrained models to video temporal grounding, where gen

Beyond Training from Scratch: Foundation Models for Data-Efficient and Generalizable Cardiac MRI Reconstruction

arXiv:2610.08109v1 Announce Type: new Abstract: Cardiac magnetic resonance imaging reconstruction aims to recover high-quality images from undersampled acquisitions, enabling faster scans while preser

Calibration Is Not Control: Intervention Value for LLM-Agent Oversight

arXiv:2606.21399v2 Announce Type: replace Abstract: Runtime oversight often intervenes when an LLM agent's calibrated failure score crosses a threshold. Yet states with the same failure risk can diffe

CALR: Continuous Anchored Latent Reasoning via Render-of-Thought Compression

arXiv:2610.07175v1 Announce Type: new Abstract: Visual latent reasoning compresses rendered derivations into compact intermediate states, reducing textual reasoning overhead. Existing approaches diffe

Catastrophic Forgetting in Sequential Thermal Anti-UAV Detection: The Role of Scale-Conditioned Gradient Imbalance

arXiv:2610.08315v1 Announce Type: new Abstract: Counter-UAV systems based on thermal infrared detection must stay accurate as operational datasets evolve, yet sequential fine-tuning causes catastrophi

Local Ai

CausalBind: Causal Modeling and Learning for Protein-Molecule Virtual Screening

arXiv:2610.07340v1 Announce Type: cross Abstract: Protein-molecule virtual screening is increasingly cast as a problem of representation learning in a shared embedding space. Existing methods rely on

local-aiarxiv-cs-ai

Closing Ambient Clinical Documentation Gaps with Automated Provider Queries

arXiv:2610.07502v1 Announce Type: new Abstract: Provider queries are clarifying requests sent by clinical documentation specialists to physicians to close gaps in the clinical note and ensure accurate

researcharxiv-cs-cl

CoDe-LoRA: Mitigating the Orthogonality Dilemma in Continual Learning of LLMs via Knowledge Consolidation and Decoupling

arXiv:2610.08312v1 Announce Type: new Abstract: Continual learning (CL) is essential for Large Language Models (LLMs) to sequentially adapt to evolving tasks. To mitigate catastrophic forgetting, rece

Commit While Futures Agree: Consequence-Aware Adaptive Action Chunking for Robot Manipulation

arXiv:2610.07949v1 Announce Type: new Abstract: Action-chunking policies predict multi-step control sequences, but a fundamental question remains: how much of a predicted action chunk should be commit

safetyarxiv-cs-ro

Complementary Supervised and Self-Supervised Representations for Out-of-Distribution Graph Learning

arXiv:2610.07628v1 Announce Type: new Abstract: Out-of-distribution (OOD) generalization remains challenging for graph neural networks (GNNs), as graph distributions can vary substantially across time

researcharxiv-cs-lg

Confidence Reasoning Graphs: Structured Confidence Estimation for LLM Agents

arXiv:2610.07948v1 Announce Type: new Abstract: When using an LLM agent in a consequential domain, making an informed decision about whether to trust its output or intervene requires calibrated confid

agentsarxiv-cs-ai

Contrastive Learning for Aspect Representation towards Explainable Recommendation

arXiv:2610.07761v1 Announce Type: cross Abstract: In this work, we propose a novel recommendation model, CLARER (Contrastive Learning for Aspect Representation towards Explainable Recommendation) that

CoRE: Learning Collaboration-Role Experts for Decentralized Collaborative Manipulation with One Policy

arXiv:2610.07752v1 Announce Type: new Abstract: Collaborative manipulation requires robots to perform complementary actions as interactions unfold. We study single-policy decentralized collaboration:

safetyarxiv-cs-ro

Cross-Lingual Activation Steering for Multilingual Language Models

arXiv:2601.16390v2 Announce Type: replace-cross Abstract: Large language models exhibit strong multilingual capabilities, yet significant performance gaps persist between dominant and non-dominant lan

Cylindrical Geodesic Flow Matching for Quasiperiodic Physiological Signal Transformation

arXiv:2610.08510v1 Announce Type: new Abstract: Paired translation between quasiperiodic physiological waveforms (i.e., recovering a target oscillatory signal from the source) is central to the interp