Search: “benchmark”

From Chains to DAGs: Probing the Graph Structure of Reasoning in LLMs

arXiv:2601.17593v3 Announce Type: replace Abstract: Recent progress in large language models has renewed interest in how multi-step reasoning is represented internally. While prior work often treats r

researcharxiv-cs-cl

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From Evaluated Models to Evaluation Aids: A Multi-Evidence Study of LLM-Based Difficulty Calibration for Programming Examinations

DGX agent

arXiv:2608.07523v1 Announce Type: cross Abstract: Difficulty differences across parallel-class programming examinations affect the fairness of course assessment. This study repositions large language

model-releasesarxiv-cs-ai

11 Aug 2026

From Semantic Grounding to Decision Optimization: A Unified Framework for Long-Horizon UAV Vision-Language Navigation

arXiv:2608.09564v1 Announce Type: cross Abstract: UAV vision-language navigation (UAV-VLN) focuses on enabling an aerial agent to follow natural-language instructions in open 3D environments from egoc

From Uncertainty to Failure Attribution: Self-Diagnosing Models for Failure Attribution under Distribution Shift

arXiv:2608.07953v1 Announce Type: new Abstract: Distribution shift poses a significant challenge to the robustness of machine learning models, but the current solutions only aim to detect out-of-distr

researcharxiv-cs-lg

Full-Feature versus Limited-Input Machine Learning for Residential Energy Estimation: A Comparative Analysis of RECS and ResStock Under Realistic Input Constraints

arXiv:2608.09255v1 Announce Type: new Abstract: Residential energy estimates are often needed before detailed envelope characteristics, equipment efficiencies, infiltration, sensor, or billing data ar

researcharxiv-cs-lg

Fusion Training for Mathematical Generalization in Large Language Models

arXiv:2608.09893v1 Announce Type: cross Abstract: Thinking Mode Fusion (TMF) enables large language models to support both concise responses and long-form reasoning by unifying a non-thinking mode and

Local Ai

GALA: Graph-Augmented LLM Agents for Root Cause Analysis and Incident Response in Microservices

arXiv:2608.08968v1 Announce Type: cross Abstract: Microservice root cause analysis (RCA) requires correlating failures across heterogeneous telemetry within complex service dependency graphs. Existing

local-aiarxiv-cs-ai

Local Ai

General OOD Detection via Model-aware and Subspace-aware Variable Priority

arXiv:2512.13003v2 Announce Type: replace-cross Abstract: Out-of-distribution (OOD) detection is essential for determining when a supervised model encounters inputs that differ meaningfully from its t

local-aiarxiv-cs-lg

GeoRoute: Geometry-Aware Hybrid Inference for Traffic Future-Frame Prediction

arXiv:2608.09493v1 Announce Type: new Abstract: Long-horizon future-frame prediction is important for autonomous driving, traffic surveillance, and intelligent transportation systems, yet remains chal

Goal-oriented Navigation Instruction Generation with Tour Video Priors

arXiv:2608.08596v1 Announce Type: new Abstract: Navigation Instruction Generation (NIG) aims to produce step-by-step natural language instructions for navigation guidance. Existing studies primarily t

Goedel-Code-Prover: Hierarchical Proof Search for Open State-of-the-Art Code Verification

arXiv:2603.19329v3 Announce Type: replace-cross Abstract: Large language models (LLMs) can generate plausible code but offer limited guarantees of correctness. Formally verifying that implementations

GraphThink: Graph-Enhanced LLM Thinking for Long-Horizon Embodied Task Planning

arXiv:2608.07905v1 Announce Type: new Abstract: Embodied agents using LLM-based planners often struggle with physical hallucinations, poor generalization to long-horizon tasks, and lack of environment

GRASP: Granularity-Aware Region Alignment and Semantic Prototype Learning for Fine-Grained Cross-Modal Understanding in Drone Views

arXiv:2608.09270v1 Announce Type: cross Abstract: Fine-grained cross-modal understanding in drone views is essential for aerial vision-language navigation. However, the inherent wide field of view and

Hierarchical Multi-Task Federated Learning in VANETs

arXiv:2608.08111v1 Announce Type: cross Abstract: Vehicular Ad hoc Networks (VANETs) increasingly rely on federated learning (FL) to enable collaborative intelligence without sharing raw sensory data.

HoloAegis: Frozen Representation, Topological Inference: Minimally Parametric Safety Manifolds for Zero-Shot LLM Guardrails

arXiv:2608.08485v1 Announce Type: new Abstract: Current LLM safety guardrails face a fundamental tension: fine-tuning distorts pre-trained representations while generative judges incur prohibitive inf

Human-Level Text-to-SQL via Reinforcement Learning on Verified Data, Without Pipeline Engineering

arXiv:2603.20004v3 Announce Type: replace-cross Abstract: Translating natural language questions to SQL queries (Text-to-SQL) is a long-standing problem in database research. Recent efforts have focus

researcharxiv-cs-cl

Hyperbolic Multimodal Continual Learning

arXiv:2608.09572v1 Announce Type: new Abstract: Hyperbolic geometry has recently emerged as a powerful representation space for multimodal learning, as it naturally captures hierarchical semantic stru

researcharxiv-cs-lg

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs

arXiv:2608.09586v1 Announce Type: new Abstract: The Independent Chip Model (ICM) converts tournament chips into reference prize equity, and policies are routinely constructed against those values. Bec

IDATA: Scalable Invertible Diffusion for Unrestricted Adversarial Transfer Attack

arXiv:2608.08734v1 Announce Type: new Abstract: Unrestricted adversarial transfer attacks are important for evaluating the black-box robustness of deep visual models. Diffusion-based attacks have show

researcharxiv-cs-cv

Illusion or Integrity? Geometrical Consistency Metric for AIGC Video Quality Evaluation

arXiv:2608.09594v1 Announce Type: cross Abstract: Recently, AI-driven video generation has attracted considerable attention. This surge increases the demand for reliable video quality assessment (VQA)

Imaginative Generative AI: Crossing the Entropy Wall into Worlds Beyond Imitation

arXiv:2608.09385v1 Announce Type: cross Abstract: Generative AI models are primarily designed to imitate the data distribution, an objective that neither corrects diversity lost by a learned generator

Implicit Virtual Leader: Decentralized Vision-Only Relative Pose Estimation for Multi-Robot Formations

model-releasesarxiv-cs-ro

arXiv:2607.15708v2 Announce Type: replace Abstract: Classical leader-follower formation control suffers from single points of failure and error propagation, and relies on absolute localization sensors

Improving Generalization Robustness of Multimodal RLVR

arXiv:2608.08802v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) makes Multimodal Large Language Models more accurate, but the gains are brittle: simply paraphrasi

InfMem: Learning System-2 Memory Control for Long-Context Agent

arXiv:2602.02704v2 Announce Type: replace Abstract: Reasoning over ultra-long documents requires synthesizing sparse evidence scattered across distant segments under strict memory constraints. While s

agentsarxiv-cs-cl

InstructionCrafter: Generating Consistent and High-Fidelity Visual Instructions

arXiv:2608.08460v1 Announce Type: new Abstract: Given textual task instructions, generating step-by-step visual instructions as an image sequence requires the simultaneous satisfaction of multiple pro

Keep It Simple: Multi-Key Episodic Memory Retrieval for Ultra-Long Video Understanding

arXiv:2608.07663v1 Announce Type: cross Abstract: When videos extend from hours to days, directly processing them end-to-end becomes impractical for current Multi-modal Large Language Models (MLLMs).

agentsarxiv-cs-ai

Kernel Methods for Refined Prophet Inequalities

model-releasesarxiv-cs-lg

arXiv:2608.08662v1 Announce Type: cross Abstract: The single-selection prophet inequality is a canonical Bayesian online selection problem in which independent nonnegative values arrive sequentially a

Knowing You Is Everything: LLM Agents Achieve Near-Perfect Profile-Consistent Reaction Prediction in Social Media Simulation

arXiv:2608.07498v1 Announce Type: cross Abstract: Autonomous AI agents in social media present concrete risks to democratic discourse and platform governance, while also offering tools for pre-deploym

Label-Free Parkinson's Disease Screening from Face and Voice through Mechanistic Interpretability

model-releasesarxiv-cs-lg

arXiv:2608.08976v1 Announce Type: new Abstract: Parkinson's disease (PD) is the second most common neurodegenerative disorder. Typical machine learning screening methods require PD labels, but the ava

LASA: Language-and-Source-Anchored Alignment for Domain Generalized Semantic Segmentation

arXiv:2608.08805v1 Announce Type: new Abstract: Domain Generalization Semantic Segmentation (DGSS) focuses on generalizing knowledge from labeled source domains to unseen target domains where data is

safetyarxiv-cs-cv

LatticeMind: A Conflict-Aware Memory Primitive for Multi-Agent Systems

arXiv:2608.08236v1 Announce Type: new Abstract: Multi-agent LLM systems often fail not for lack of candidate answers, but because they have no persistent mechanism for deciding which incompatible clai

agentsarxiv-cs-ai

Learning Deep Modality-Shared Self-Expressiveness for Image Clustering with Textual Information

arXiv:2608.08418v1 Announce Type: new Abstract: Leveraging textual information for image clustering has emerged as a promising direction, largely owing to the powerful representations learned by Visio

safetyarxiv-cs-cv

Learning from Consensus and Disagreement: Unsupervised On-Policy Self-Distillation with Minority-Trajectory Contrast

arXiv:2608.08764v1 Announce Type: cross Abstract: On-policy self-distillation improves language-model reasoning by querying a teacher on states actually visited by the student. Recent methods create a

Learning How the World Evolves: Extrapolative Video World Models via Latent Dynamics Reasoning

arXiv:2608.09926v1 Announce Type: new Abstract: The world evolves following its dynamics, i.e., its laws of motion. However, leading video diffusion models largely fit the pixels without modeling how

Learning Structural Illumination for Unsupervised Low-light Enhancement

arXiv:2608.08153v1 Announce Type: new Abstract: Existing unsupervised low-light image enhancement (LLIE) methods often estimate illumination directly from the entire low-light input, without separatin

Learning to Triage Vulnerability Reports from Program Analysis: An Empirical Study in Node.js

model-releasesarxiv-cs-lg

arXiv:2510.20739v2 Announce Type: replace-cross Abstract: Program analysis tools often produce large volumes of candidate vulnerability reports that require costly manual review, creating a practical

LEGO-Puzzles: How Good Are MLLMs at Multi-Step Spatial Reasoning?

arXiv:2503.19990v4 Announce Type: replace Abstract: Many real-world applications of spatial intelligence, such as robotic control, autonomous driving, and automated assembly, require spatial reasoning

Tutorials

Let Geometry GUIDE: Layer-wise Unrolling of Geometric Priors in Multimodal LLMs

arXiv:2604.05695v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable progress in 2D visual tasks but still struggle to understand physical space in rea

tutorialsarxiv-cs-cv

LF{}^{2}AR: Accounting for Layerwise Dynamics to Improve Multimodal Adaptation of Language Models

arXiv:2503.06211v3 Announce Type: replace-cross Abstract: Text-pretrained language models (LMs) encode rich world knowledge, but adapting them to process and generate perceptual modalities such as aud

LGNNIC: Acceleration of Large-Scale GNN Training using SmartNICs

arXiv:2608.07733v1 Announce Type: cross Abstract: Graph Neural Networks (GNNs) are widely used across domains such as natural sciences, social network analysis, chip design, and recommendation systems

LibraSpec: Dynamic Diffusion-Based Speculative Decoding via Marginal-Gain-Driven Optimization

arXiv:2608.08721v1 Announce Type: cross Abstract: Speculative decoding accelerates large language model inference by drafting multiple tokens for parallel verification, with efficiency critically dete

Applications

LineGraph2Road: Structural Graph Reasoning on Line Graphs for Road Network Extraction

arXiv:2602.23290v2 Announce Type: replace Abstract: Extracting routable road networks from satellite imagery requires accurate topology recovery beyond pixel-level segmentation. Recent methods decompo

applicationsarxiv-cs-cv

LogiShot: Logically Coherent Cross-Shot Video Generation

arXiv:2608.08820v1 Announce Type: new Abstract: Generating cross-shot videos that are logically connected is essential for content creation. Currently, most cross-shot video-generation workflows, such

Long SKILL Compliance as Logical Reasoning: Closure-Grounded Detection with Scaling-Guided On-Policy Distillation

arXiv:2608.08146v1 Announce Type: new Abstract: The increasing complexity of enterprise business scenarios has promoted the widespread adoption of long SKILL documents in agent systems, posing new cha

LookME: Lookup-Based Multimodal Embeddings for Layer Injection in Vision-Language Models

arXiv:2607.16305v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) have achieved strong progress in multimodal understanding. However, scaling dense or sparse Mixture-of-Experts (

LoRA-based Adaptation Alone Is Not Enough: Understanding the Limits of Foundation Models for Face Presentation Attack Detection

arXiv:2608.09633v1 Announce Type: new Abstract: Face presentation attack detection (PAD) aims to reliably detect a wide range of presentation attacks. While PAD methods achieve strong performance with

researcharxiv-cs-cv

M^3Prune: Hierarchical Communication Graph Pruning for Efficient Multi-Modal Multi-Agent Retrieval-Augmented Generation

arXiv:2511.19969v2 Announce Type: replace Abstract: Recent advancements in multi-modal retrieval-augmented generation (mRAG), which enhance multi-modal large language models (MLLMs) with external know

agentsarxiv-cs-ai

Local Ai

Macaron-V1: Towards Open Continual Learning with Self-Improvement and Mixture-of-LoRA

arXiv:2608.09819v1 Announce Type: cross Abstract: Macaron-V1 is an open agent-model family for experiential intelligence: learning from experience in real environments and continuing to learn after de

local-aiarxiv-cs-cl