Search: “benchmark”

Learning from What You Retrieve: Online RL Fine-Tuning for Semantic Retrieval

arXiv:2608.30753v1 Announce Type: cross Abstract: In large-scale e-commerce retrieval, dual-encoder retrievers are op- timized for contrastive similarity, whereas downstream rerankers capture finer-gr

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Learning Materials Properties from Scarce Labels and Unlabeled Crystals

DGX agent

arXiv:2608.30682v1 Announce Type: cross Abstract: Learning materials properties from scarce labels and unlabeled crystals is a central challenge for data-driven materials discovery. We present SemiMat

model-releasesarxiv-cs-ai

1 Sept 2026

Learning PDE Time-Stepping with Neural Cellular Automata

arXiv:2608.30328v1 Announce Type: new Abstract: Classical numerical solvers for partial differential equations (PDEs) are computationally expensive to solve repeatedly across varying initial condition

Agents

Learning Simple Test-Time Environments for LLM Web Agents

arXiv:2608.29305v1 Announce Type: cross Abstract: Large language model (LLM) agents have demonstrated remarkable proficiency in manually constructed environments, yet their performance frequently coll

agentsarxiv-cs-ai

Learning the Geometry of Admissible Hypotheses through Inductive Bias in Training Distributions

arXiv:2608.31028v1 Announce Type: cross Abstract: Scientific discovery often requires reasoning over competing hypotheses that are consistent with experimental observations. For mixed-variable and com

Learning to Follow In-Context Watermark Instructions via Self-Distillation

arXiv:2608.29030v1 Announce Type: new Abstract: In-context watermarking (ICW) prepends an instruction to a query asking the model to embed a statistically detectable signal in its response. It thus eq

Learning to Restore More: Continual Capability Expansion for Pretrained Image Restoration Models

arXiv:2608.30305v1 Announce Type: new Abstract: Image restoration models are typically trained with a fixed set of capabilities. When new restoration requirements emerge, existing solutions usually tr

researcharxiv-cs-cv

Learning Where Outcomes Change:Credit-Addressable Reasoning for Multimodal Geometry

arXiv:2608.30457v1 Announce Type: cross Abstract: Multimodal geometry reasoning requires VLMs to extract precise visual relations and preserve them through multi-step deduction. Existing free-form tra

researcharxiv-cs-cl

LightNav-0: Eliciting VLM Spatial Intelligence for Generalist Embodied Navigation

arXiv:2608.30935v1 Announce Type: cross Abstract: Embodied navigation requires agents to translate heterogeneous goals and visual observations into actions across tasks, environments, and robot embodi

applicationsarxiv-cs-ai

LISynSeg: Data-Centric Label-to-Image Synthesis for Cross-Modality Whole-Heart Segmentation

model-releasesarxiv-cs-cv

arXiv:2608.31073v1 Announce Type: new Abstract: Whole-heart segmentation (WHS) in computed tomography (CT) and magnetic resonance imaging (MRI) is affected by acquisition shifts and heterogeneous card

LLM Post-Training as Brownfield Maintenance: An Industrial Perspective on Dataware Engineering

arXiv:2608.31102v1 Announce Type: cross Abstract: Industrial post-training is a brownfield regime. Teams inherit a deployed checkpoint and must land targeted improvements under fixed compute and mixtu

LLMODE: Aligning ODEs with LLMs via Gated Token Injection for Irregular Spatio-Temporal Forecasting

arXiv:2608.29640v1 Announce Type: cross Abstract: Large language models (LLMs) have shown promise for spatio-temporal forecasting, but existing approaches often rely on regularly sampled token sequenc

applicationsarxiv-cs-ai

Localizing Emergent Failures in Agentic AI: Recovering Minimal Repair Families via Counterfactual Replay

arXiv:2608.29228v1 Announce Type: new Abstract: Failures in agentic AI systems can arise from interactions among messages exchanged by multiple large language model (LLM) agents. Pointwise attribution

LOCI: A Locator-Critic with Refinement Loop

arXiv:2608.30959v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) still struggle on tasks requiring complex visual understanding. We argue that the core issue is not high-level reasoning

Locked at the Entrance, Open Inside: Where RLVR Narrows the Solution Space

arXiv:2608.29188v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) substantially improves single-sample accuracy (pass@1) but causes the policy's solution space to

LongGuard: Mechanistic Analysis and Training-Free Mitigation of Long-Context Failure in Safety Guardrails

arXiv:2608.27580v2 Announce Type: replace Abstract: Safety guardrails serve as the last line of defense against harmful inputs and outputs of large language models (LLMs), yet they are trained and eva

Machine Learning-Enhanced Tabu Search for Tactical Wireless Network Design

arXiv:2608.28627v1 Announce Type: new Abstract: Designing high-performance tactical wireless networks under realistic operational constraints gives rise to challenging combinatorial optimization probl

ManGo: Manga Active Narrative Grounding Optimization

arXiv:2608.29865v1 Announce Type: new Abstract: Manga visual question answering requires models to answer questions over panel-based visual narratives, where relevant evidence is distributed across or

safetyarxiv-cs-cl

Medical Foundation Model Features as Perceptual Loss for Brain MRI Contrast Dose Simulation

arXiv:2608.28773v1 Announce Type: cross Abstract: Perceptual losses are widely used in medical image synthesis because they encourage agreement in high-level structure beyond voxel-wise intensity simi

researcharxiv-cs-cv

MEL: Coordinate-Preserving EEG Tokenization for fMRI Translation

arXiv:2608.29304v1 Announce Type: new Abstract: Translating electroencephalography (EEG) into functional magnetic resonance imaging (fMRI) is important for medical neuroimaging, clinical brain-state m

researcharxiv-cs-lg

MI-Distillation: Selecting from Model-Interpolated Instruct-Reasoning Data Spectrum for Chain-of-Thought Distillation

arXiv:2608.29623v1 Announce Type: cross Abstract: Recent advances in large reasoning models (LRMs) have shown strong performance on complex problems through long chain-of-thought (Long CoT) reasoning.

More Perspectives, Stronger Signals: Multi-Perspective Enhancement and Progressive Fusion for Multimodal Entity Representation Learning

arXiv:2608.29139v1 Announce Type: new Abstract: Learning effective multimodal entity representations is fundamental for reasoning tasks such as multimodal knowledge graph completion (MMKGC). However,

Multimodal Adaptive Expert Selection with Text Routing and Ordinal Prototype Optimization for Sentiment Analysis

arXiv:2608.30726v1 Announce Type: new Abstract: Multimodal Sentiment Analysis (MSA) is a fundamental component of affective computing that aims to decipher complex emotional states by integrating verb

MVID: Feed-Forward Multi-View Intrinsic Image Decomposition

arXiv:2512.23667v3 Announce Type: replace Abstract: Intrinsic image decomposition aims to recover material and illumination factors from RGB observations, but real-world images entangle reflectance wi

applicationsarxiv-cs-cv

New Model: Spark-X2.5-4B, Spark-X2.5-1.7B

model-releasesr-localllama

I was browsing HF for small LLMs and run into this model. It does not seem to be a fine tune - the model has its own architecture. https://huggingface.co/XHToken/Spark-X2.5-1.7B https://huggingface.co

Not All or None: Dynamic Construction of Target-aware Memory Graph for Conversational Stance Detection

arXiv:2608.29066v1 Announce Type: cross Abstract: Stance detection is crucial for understanding the underlying attitude of an expression towards a target. Conversational stance detection is a more cha

applicationsarxiv-cs-ai

Not Safe for All: Auditing the Dialect Penalty in Text-to-Image Safety Pipelines

arXiv:2608.29589v1 Announce Type: new Abstract: Text-to-image (T2I) safety guardrails fail to generalize equitably to non-standard dialects. Evaluating 23,080 paired prompts across five English dialec

Null-Space Diffusion Restoration with Adaptive Uncertainty-Guided Fusion for Ultrasound Speckle Reduction

model-releasesarxiv-cs-cv

arXiv:2608.29820v1 Announce Type: new Abstract: Ultrasound B-mode imaging commonly suffers from speckle noise and artifacts, requiring a delicate balance between contrast, resolution, and preservation

NVE: A Separability and Coverage-Aware Internal Validation Metric for Biclustering

arXiv:2608.29045v1 Announce Type: new Abstract: Biclustering, or co-clustering, aims to discover coherent submatrices by grouping rows and columns of a data matrix simultaneously. This local two-dimen

researcharxiv-cs-lg

OCR-Based Field Extraction for Archaeological Pottery Metadata: The CENTURIA Dataset

arXiv:2608.30616v1 Announce Type: new Abstract: Pottery is a primary source for reconstructing the chronological and economic dimensions of past societies. Archaeologists often document ceramic finds

researcharxiv-cs-cv

Off-Context GRPO: Learning to Reason on Hard Problems using Privileged Information

arXiv:2607.19313v2 Announce Type: replace-cross Abstract: Reinforcement learning with verifiable rewards (RLVR) improves reasoning in large language models. Yet, typical RLVR approaches fail on diffic

On the Resilience of Text-to-Video Diffusion Models to Hardware Faults

arXiv:2608.29598v1 Announce Type: new Abstract: We present the first systematic study of the resilience of text-to-video (T2V) diffusion models under random hardware-level faults. While T2V models are

OntoAligner-Ensemble: Voting-Based Fusion across Heterogeneous Ontology Alignment Techniques

arXiv:2608.31137v1 Announce Type: new Abstract: Ontology alignment (OA) has evolved through several methodological paradigms, ranging from lexical and structural aligners to knowledge graph embedding

OPAL: Orthonormal Prototype Alignment Learning for Interpretable Image Classification

arXiv:2608.30003v1 Announce Type: new Abstract: Prototypical part-based models provide explainable predictions by comparing input regions to learned prototypes. However, current approaches are burdene

safetyarxiv-cs-cv

Local Ai

OptiGeo: Efficient Monocular Geometry for Embodied Perception in Optically Challenging Scenes

arXiv:2608.29881v1 Announce Type: new Abstract: Monocular depth estimation has achieved strong open-domain generalization, yet reliable robotic deployment remains difficult in transparent, reflective,

local-aiarxiv-cs-cv

Agents

ORDDAR: Observation-Driven Reasoning for Distortion-Resilient Decision, Action, and Cognitive Recovery

arXiv:2608.28704v1 Announce Type: new Abstract: AI agents increasingly perform long-term reasoning, planning, tool use, memory integration, and autonomous decision making, yet erroneous intermediate s

agentsarxiv-cs-ai

PAGE-RAG: Provenance-Aware Graph Evidence Promotion for Fixed-Budget Multi-hop Retrieval-Augmented Generation

arXiv:2608.29753v1 Announce Type: new Abstract: Multi-hop question answering in retrieval-augmented gener?ation (RAG) often benefits from retrieving beyond the few candidates that will finally be read

Paper Pilot: A Human-in-the-Loop Expert System for Evidence-Traceable Scientific Manuscript Generation in Applied Sciences

arXiv:2608.28596v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly embedded in scientific workflows for literature analysis, drafting, and review. Existing systems adva

PAVE: Predictive Alignment and Value-Guided Evolution for World-Action Policies

arXiv:2608.30378v1 Announce Type: cross Abstract: Direct vision-language-action policies generate continuous robot actions efficiently, but standard behavior cloning leaves two complementary gaps: the

PhasorNet: Learning Structure from Frequency for Real-Time Stereo Matching

model-releasesarxiv-cs-cv

arXiv:2608.29819v1 Announce Type: new Abstract: Accurate stereo matching remains challenging in ill-posed regions such as fine structures, reflective, or transparent objects, where appearance cues are

PhyloGFN: Phylogenetic inference with generative flow networks

arXiv:2310.08774v3 Announce Type: replace-cross Abstract: Phylogenetics is a branch of computational biology that studies the evolutionary relationships among biological entities. Its long history and

Local Ai

PhysVR: Vision-Language Model Guided Interference-aware Temporal Feature Refinement for Remote Physiological Measurement

arXiv:2608.29663v1 Announce Type: new Abstract: Remote photoplethysmography (rPPG) enables contactless physiological measurement from facial videos, yet its subtle pulse-related variations are easily

local-aiarxiv-cs-cv

PLC-DPO: Posterior Label Correction in Noisy and Ambiguous Preference Optimization

model-releasesarxiv-cs-cl

arXiv:2608.30597v1 Announce Type: cross Abstract: Direct Preference Optimization (DPO) simplifies alignment through pairwise comparisons but assumes all observed preferences are reliable. Real data of

Polis: 3D Self-Supervision at City Scale

arXiv:2608.29426v1 Announce Type: cross Abstract: Reliable semantic representations derived from city-scale 3D models are increasingly important for urban analysis, infrastructure monitoring, autonomo

Predicting Residential Rents in Dakar Using Machine Learning

arXiv:2608.30865v1 Announce Type: new Abstract: Dakar's residential rental market remains poorly documented despite its economic and social importance: 54.4% of households are renters, compared to 23.

Pro-Router: Token-Aware Progressive Model Routing with Adaptive Edge-Cloud Collaboration for Efficient Multimodal LLM Inference

arXiv:2608.28726v1 Announce Type: new Abstract: The remarkable performance of multimodal large language models (MLLMs) comes at the cost of substantial computational overhead, posing significant chall

Propensity Straight-Through Gradients for Discrete Stochastic Systems

arXiv:2608.25631v1 Announce Type: cross Abstract: Continuous-time Markov chains (CTMCs) provide the backbone for modeling discrete stochastic dynamics across applied, physical, and biological sciences

Randomized YaRN Improves Length Generalization for Long-Context Reasoning

arXiv:2606.23687v2 Announce Type: replace Abstract: Large language models (LLMs) are typically pretrained on short sequences and then extended to work on longer sequences with additional training. How

researcharxiv-cs-cl