Search: “benchmark”

A homotopy-type-theoretic generalization of neurosymbolic inference

arXiv:2606.17851v2 Announce Type: replace Abstract: A wide range of neurosymbolic (NeSy) systems compute one functional: a belief-weighted sum of a logical quantity over a space of sigma-structures, o

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Model Releases

A Study of the Design Space of Motion and Disocclusion Control in Video Generation

DGX agent

arXiv:2512.13392v3 Announce Type: replace Abstract: Disocclusion occurs when object movement reveals previously hidden content. Existing image-to-video methods provide different forms of motion and di

model-releasesarxiv-cs-cv

1 Sept 2026

ACTD: Anchor-Based Cross-Tokenizer Distillation with Residual Regularization

arXiv:2608.29662v1 Announce Type: new Abstract: Knowledge distillation effectively transfers reasoning capabilities from large language models to lightweight student models. To enable knowledge transf

safetyarxiv-cs-cl

ActiveAugment: Online Active Learning for Augmentation Selection in Deep Learning

arXiv:2608.28923v1 Announce Type: cross Abstract: Data augmentation is a cornerstone of deep learning pipelines, yet existing strategies treat it as a static, model-agnostic preprocessing step, either

Adaptive Multi-Branching for Shallow Decision Tree Induction

arXiv:2608.29262v1 Announce Type: cross Abstract: Decision trees are attractive for tabular prediction tasks because each prediction follows an interpretable sequence of feature-threshold tests. Under

AdaVLA: Adaptive Step Flow Matching for Training-free Acceleration of Vision-Language-Action Models

model-releasesarxiv-cs-lg

arXiv:2608.29208v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models, built upon Vision-Language Models (VLMs), have significantly enhanced robotic capabilities by leveraging internet

Agent Zero Memory: Provenance-Aware Long-Term Memory for LLM Agents

arXiv:2608.29606v1 Announce Type: new Abstract: Large language model (LLM) agents need durable, faithful memory of everything a user or organization has said and stored, yet most memory systems commit

agentsarxiv-cs-cl

AgenticRag-R1: Agentic Reinforcement Learning with Stack Memory for Multi-Step Reasoning, Retrieval and Memorizing

arXiv:2608.29622v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) improves the factuality of large language models (LLMs), yet existing RAG systems often struggle with complex, mu

AGM: Achievement-Grounded Memory for Closed-Loop Agents with Frozen VLA Policies

arXiv:2608.29537v1 Announce Type: cross Abstract: Frozen vision-language-action (VLA) policies offer broad manipulation skills but execute open-loop action chunks without tracking task progress, so th

Agora: Enhancing LLM Agent Reasoning Via Auction-Based Task Allocation

arXiv:2607.09600v2 Announce Type: replace Abstract: Enhancing the reasoning capabilities of large language model (LLM) agents requires effective orchestration of diverse expert models and tools. Howev

agentsarxiv-cs-ai

All You Need Is Non-Commutative Words

model-releasesarxiv-cs-cl

arXiv:2608.29314v1 Announce Type: new Abstract: We represent lexical tokens as unitary matrices and encode each sentence as their ordered product. The noncommutativity of matrix product captures word

Amortized Anchor Refinement for Deployable Continuous-Time 4D Gaussian Reconstruction

model-releasesarxiv-cs-cv

arXiv:2608.30218v1 Announce Type: new Abstract: Continuous-time 4D reconstruction remains impractical on standalone XR headsets. Per-scene optimization demands deployment-infeasible compute, and lower

An Open-Source, Event-Driven Pipeline for Cryptocurrency Market Data: Ingestion, Forecasting, and On-Chain Fraud Detection

arXiv:2608.29973v1 Announce Type: new Abstract: Cryptocurrency markets generate high-frequency, multi-source data that is expensive to work with unless a team already has commercial-grade streaming an

Anomaly Detection on Small Industrial Components via Vision-Based Tactile Sensing

arXiv:2608.30506v1 Announce Type: new Abstract: Automated inspection of small industrial components, including sub-centimetre-scale parts where defects are geometry-driven and poorly resolved by stand

researcharxiv-cs-ro

Anthropic launches Claude Fable 5.1 after inking $35B cloud deal with Lambda

model-releasessiliconangle

Anthropic PBC today debuted Claude Fable 5.1 and Claude Mythos 5.1, its most capable large language models to date. The launch comes a day after the company inked a 35 billion infrastructure deal with

AnyWorld: Factorized Egocentric World Models for Cross-Embodiment Generalization

model-releasesarxiv-cs-ro

arXiv:2608.29242v1 Announce Type: new Abstract: Collecting contact-rich robot experiences at scale remains a major bottleneck for generalizable manipulation. Beyond data quantity, robot learning also

Applications

AOI-Net: Structural Face AOI-Guided Eye-Gaze Track Representation Learning for Autism Spectrum Disorder Detection

arXiv:2608.29289v1 Announce Type: cross Abstract: Eye-movement tracking has emerged as a promising non-invasive approach to Autism Spectrum Disorder (ASD) screening, with systematic differences in att

applicationsarxiv-cs-ai

APIFlow-Bench: Measuring Whether Agents Survive Long, Dependent API Workflows

arXiv:2608.29128v1 Announce Type: new Abstract: Tool-using agents are commonly evaluated by a single bit: whether an end-to-end workflow completed. This metric fails to distinguish failures that matte

Argument-Aware Semantic Alignment of Normative Texts: A Toulmin-Based Neuro-Symbolic Approach

arXiv:2608.29529v1 Announce Type: cross Abstract: Semantic alignment between specialized normative texts is challenging when equivalent requirements use different terms, syntax, and levels of abstract

Tutorials

ARMOR: Manifold-Oriented Training for Adversarially Robust Aerial Object Detection under Data Scarcity

arXiv:2608.29510v1 Announce Type: new Abstract: Aerial object detection is increasingly deployed in real-world applications, but models remain vulnerable to physical, universal adversarial patches tha

tutorialsarxiv-cs-cv

Applications

Asymmetric Phase Coding Video Watermarking

arXiv:2608.29212v1 Announce Type: cross Abstract: Existing video watermarking systems are symmetric: the party that can verify a mark holds the extractor weights or generator secret and can therefore

applicationsarxiv-cs-cv

AutoCRAT: Within-trajectory Joint Control of Stochasticity and Compute for LLM Reasoning

arXiv:2608.29988v1 Announce Type: new Abstract: Large language models (LLMs) achieve strong reasoning performance, which depends critically on inference-time decisions. Yet these decisions are commonl

Autoregressive Mosaics: Probing 2D Spatial Reasoning in Text-Only Language Models

arXiv:2608.30751v1 Announce Type: new Abstract: Large language models (LLMs) trained only on text and code can sometimes generate programs that draw recognizable images. However, it is unclear whether

BAITBENCH: Measuring Agent Reward Hacking with Optional Shortcuts Planted in ML Tasks

arXiv:2608.30724v1 Announce Type: cross Abstract: LLM agents are increasingly used to run autonomous ML experiments, iterating on target metrics with little human oversight. Prior work has documented

Banger paper from the Qwen team. If you evaluate agents on anything longer than a single session, this one is worth your time. (bookmark it)…

Banger paper from the Qwen team. If you evaluate agents on anything longer than a single session, this one is worth your time. (bookmark it) E-Commerce Bench runs an agent through a simulated 365-day

model-releasesdair-ai--x

Beyond Dense States: Sparse Transcoders as Causally Testable Operators for LLM Latent Reasoning

arXiv:2602.01695v2 Announce Type: replace Abstract: Latent reasoning reduces the token-generation cost of chain-of-thought reasoning by replacing explicit intermediate tokens with continuous latent tr

Beyond NL2Code: A Structured Survey of Multimodal Code Intelligence

arXiv:2606.15932v3 Announce Type: replace Abstract: While Large Language Models (LLMs) have substantially advanced text-to-code generation, many real programming tasks specify intent through visual ar

agentsarxiv-cs-cl

Beyond Static Visual Tokens: Structured Sequential Visual Chain-of-Thought Reasoning

arXiv:2603.26737v2 Announce Type: replace-cross Abstract: Current multimodal LLMs encode images as static visual prefixes and rely on text-based reasoning, lacking goal-driven and adaptive visual acce

Beyond the Answer Key: Robustness Evaluation of Large Language Models for Step-Level Mathematical Verification

arXiv:2608.28725v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as graders, verifiers, and process auditors, but most mathematical evaluations still emphasize final-

Beyond Token-Level Guidance: Inference-Time Alignment of Specialized LLMs via Cross-Family Representation Steering

arXiv:2608.30319v1 Announce Type: cross Abstract: Large language models (LLMs) finetuned for specialized domains represent crucial high-impact applications. Inference-time alignment improves safety de

Beyond Uncertainty: Multi-Solver Disagreement Rewards for Self-Evolving Reasoning Curricula

arXiv:2608.30035v1 Announce Type: new Abstract: Self-evolving reasoning frameworks train a Challenger to generate questions exposing a Solver's weaknesses, creating adaptive curricula without human da

Beyond Visual Boundaries: Rethinking Scene Segmentation for Movie RAG

arXiv:2608.28699v1 Announce Type: new Abstract: Understanding long-form video remains a fundamental challenge for multimodal large language models (MLLMs). Sparse frame sampling fails to capture fine-

researcharxiv-cs-cv

BiasMix-Finance: Post-Generation KYC Guardrails for LLM Portfolio Advice

arXiv:2608.28646v1 Announce Type: new Abstract: Large language models (LLMs) can generate plausible-sounding ETF portfolios while silently violating basic KYC-style constraints on risk, fees, and dive

Breaking the Code: Security Assessment of AI Code Agents Through Systematic Jailbreaking Attacks

arXiv:2510.01359v3 Announce Type: replace-cross Abstract: Code-capable large language model (LLM) agents are embedded in software engineering workflows where they can read, write, and execute code, ra

Budget-Aware Compression Pipeline for Single-GPU LLM Inference: Methods, Trade-offs, and Coupling Effects

model-releasesarxiv-cs-cl

arXiv:2608.30076v1 Announce Type: new Abstract: Single-GPU deployment of 70B-parameter language models on an NVIDIA GPU is constrained by device memory, long-context throughput, and engineering integr

Call Neighbours Yourself: Graph Walks with Destination-Conditioned On-Policy Self-Distillation

arXiv:2608.29588v1 Announce Type: new Abstract: Reasoning over text-attributed graphs (TAGs) requires large language models (LLMs) to combine a node's text with evidence distributed across its neighbo

Can escalation channels redirect reward hacking toward defect disclosure?

arXiv:2608.29460v1 Announce Type: new Abstract: When coding agents encounter defective test infrastructure they may reward-hack: hardcoding outputs or editing test files to pass tests they cannot legi

Candidate supply and answer selection shape the value of LLM judging in multi-agent systems

arXiv:2608.25937v2 Announce Type: replace Abstract: Multi-agent systems (MAS) sometimes already have the potential to answer correctly, but still report a wrong answer. Explaining this outcome is diff

agentsarxiv-cs-ai

CANVAS: Consistency-Aware Navigation via Visual Adaptive Sampling for Long-Context Text-to-SVG Generation

arXiv:2608.30689v1 Announce Type: new Abstract: Autoregressive large models have recently advanced Text-to-SVG generation from simple icons to complex, long-context graphics, yet standard autoregressi

researcharxiv-cs-cv

Capability-Stratified Degradation in Ternary Language Models

arXiv:2608.28809v1 Announce Type: new Abstract: Extreme low-bit inference offers a route toward smaller models and constrained deployment. Ternary language models restrict weights to {-1,0,+1}, approa

CARVE: Verified Expansion for Variable-Length Generation in Diffusion Language Models

arXiv:2608.30922v1 Announce Type: new Abstract: Masked diffusion language models predict tokens from a partially observed response canvas, enabling bidirectional conditioning and parallel token refine

CAST: Critique-Aware Supervision for Training Reliable Long-Horizon Tool-Calling Agents

arXiv:2608.30147v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly deployed in long-horizon, interactive, and stateful environments. In these settings, a single wrong a

safetyarxiv-cs-cl

CateKV: On Sequential Consistency for Long-Context LLM Inference Acceleration

arXiv:2608.30295v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated strong capabilities in handling long-context tasks, but processing such long contexts remains challengi

CDPR: Counterfactual Advantage-based Credit Assignment for Cost-Aware Sequential Medical Diagnosis

arXiv:2608.28599v1 Announce Type: new Abstract: Clinical diagnosis is a step-by-step, cost-aware process: a physician orders examinations one at a time, observes the results, and updates the diagnosis

Centering before Pruning: Lightweight Geometry Correction for Diversity-Based Visual Token Pruning in LVLMs

arXiv:2608.30263v1 Announce Type: cross Abstract: Large vision-language models (LVLMs) incur substantial inference costs due to their long and highly redundant visual-token sequences. Diversity-based

Chat-Edit-3D++: Interactive 3D and 4D Scene Editing via Large Language Models

arXiv:2608.29137v1 Announce Type: new Abstract: Recent work on image content manipulation based on vision-language pre-training models has been effectively extended to text-driven 3D scene editing. Ho

agentsarxiv-cs-cv

Local Ai

CineForge: Self-Improving Agents for Long-Horizon Video Generation

arXiv:2608.29621v1 Announce Type: cross Abstract: Long-horizon story-driven video generation requires a production agent to coordinate narrative decomposition, state tracking, shot design, prompt cons

local-aiarxiv-cs-ai

ClearText-Video: A Large-Scale Text-Centric Video Dataset Bridging Video Restoration and Scene-Text Enhancement

model-releasesarxiv-cs-cv

arXiv:2608.28784v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have recently made strong progress in visual--linguistic understanding. However, their performance on text-cent