Search: “benchmark”

On-Policy Distillation Meets Off-Policy GRPO: Training Compact Instruction-Following Rerankers

arXiv:2609.01947v1 Announce Type: cross Abstract: Compact instruction-following rerankers are attractive for deployment, but conventional distillation pipelines typically train students by offline imi

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Tutorials

Oracle, will I ever learn? A study of prediction convergence and complementarity across link prediction models

DGX agent

arXiv:2609.02638v1 Announce Type: new Abstract: Knowledge graphs have become an important source of structured knowledge for Web applications, including search, question answering, and recommender sys

tutorialsarxiv-cs-lg

3 Sept 2026

OSDAG: Online Scheduling for Efficient Multi-Robot Collaboration

model-releasesarxiv-cs-ro

arXiv:2606.15255v2 Announce Type: replace Abstract: Coordinating heterogeneous multi-robot systems (MRS) for complex, long-horizon tasks requires both flexible high-level reasoning and efficient execu

OutageDiT: A Generative Foundation Model for Power Outage Forecasting and Scenario Simulation

arXiv:2609.01896v1 Announce Type: cross Abstract: Power-outage planning requires scenarios before an event occurs. These scenarios must represent uncertainty in magnitude, timing, and duration while p

Tutorials

PEARL: Path-Entity Aligned Relational Learning with Contextual Subgraphs for Inductive Knowledge Graph Completion

arXiv:2609.02216v1 Announce Type: new Abstract: Inductive knowledge graph completion (IKGC) aims to predict missing links involving entities unseen during training, requiring models to learn transfera

tutorialsarxiv-cs-ai

Perceptually Regularized Diffusion Model for Image Super-Resolution

arXiv:2609.02016v1 Announce Type: cross Abstract: Image super-resolution, which aims to reconstruct high-resolution images from their low-resolution observations, is fundamental to medical imaging, re

PIE-APT: Abductive Planning over Temporal Dynamic Knowledge Graphs via Incremental Reasoning

arXiv:2607.27287v2 Announce Type: replace Abstract: Planning over Temporal Dynamic Knowledge Graphs (TDKGs) presents theoretical challenges in open-world environments with incomplete information. Exis

Plenoptic Condensation: A Novel Approach to Generalized Scene Reconstruction

arXiv:2607.18151v2 Announce Type: replace Abstract: We present a novel Generalized Scene Reconstruction (GSR) approach called Plenoptic Condensation (PCon). PCon uses a multi-stage reconstruction pipe

researcharxiv-cs-cv

Post-Training Ternarization of Qwen3-4B Capability, Effective Bit Budget, Storage Compression, and Deployment

arXiv:2609.01962v1 Announce Type: new Abstract: Ultra-low-bit language models can reduce storage and memory bandwidth, but a nominal '1.58-bit' label does not fully describe the stored representation,

Predict, Don't Iterate: Efficient Adaptive-Length Infilling for Diffusion Language Models

arXiv:2609.02108v1 Announce Type: cross Abstract: Diffusion language models (DLMs) have emerged as a promising alternative to the auto-regressive paradigm. With bidirectional attention and any-order g

PRO-Step: Step-level Process Reward Optimization for Retrieval-Augmented Generation

arXiv:2609.01658v1 Announce Type: cross Abstract: Retrieval-Augmented Generation enhances Large Language Models by grounding responses in external knowledge, but multi-hop reasoning remains vulnerable

Prompt-Space Meta-Learning Does Not Transfer Across Users: A Frozen-LLM Negative Result

arXiv:2609.01615v1 Announce Type: new Abstract: Personalizing a frozen large language model (LLM) to individual users is often framed as a meta-learning problem in prompt space: each user is a task, a

safetyarxiv-cs-lg

ProSR: Semantic-Prototype-Guided Discrete Modeling for Physically Consistent SAR Super-Resolution

arXiv:2609.02377v1 Announce Type: new Abstract: High-resolution Synthetic Aperture Radar (SAR) imagery is critical for precision analysis such as automatic target recognition, yet its acquisition is c

Quantum MeanFlow: single-shot generative sampling on NISQ hardware

arXiv:2609.02186v1 Announce Type: cross Abstract: Quantum generative models offer a promising framework for exploring whether quantum computation can enhance generative machine learning. Flow matching

Qwen3.8-Flash-Next MTP merged in ik_llama.cpp (integrated head or separate -md file)... 45 → 90 tok/s on a 5090 + 128GB, works down to a 12GB 4070

model-releasesr-localllama

ik_llama.cpp merged qwen4exp MTP support yesterday (PR #2369, mine, reviewed and tested by four other people on their own hardware). It's on main now, no fork or patch needed. Posting since the last c

Local Ai

RAFT-DVC: Resolution-Aware Machine Learning-Based Digital Volume Correlation

arXiv:2609.01876v1 Announce Type: new Abstract: Digital volume correlation (DVC) provides three-dimensional full-field displacement measurements from volumetric images, but how the internal resolution

local-aiarxiv-cs-cv

[RELEASE] - SupraGDN-5M - a tiny GatedDeltaNet model competing with other community while models trained on MUCH less data!

model-releasesr-localllama

https://preview.redd.it/5rs3d7vtgbnh1.png?width=950&format=png&auto=webp&s=df828c1146bc6167bd09d3300018aba426fc1ab2 Hey, r/LocalLLaMA ! We are releasing SupraGDN-5M. It's a tiny GatedDeltaNet (GDN1) b

SafeEvolve: Harness-Policy Co-Evolution from Agent Experience for Safety Alignment

arXiv:2609.02786v1 Announce Type: new Abstract: The performance of LLM-based agents is jointly shaped by the base model and the harness used when interacting with the environment. This exposes them to

SALA: Semantic-Aware Logical Alignment for Complex Reasoning in In-Context Learning

arXiv:2609.02336v1 Announce Type: new Abstract: Effective in-context learning (ICL) for complex reasoning relies on selecting the right demonstrations. Traditional retrieval methods based on surface s

Scalable Bayesian Optimization of Composite Functions for Image-Based Inverse Problems in Materials Characterization

arXiv:2609.02126v1 Announce Type: new Abstract: Estimating physical parameters from scientific images is a common inverse problem in materials characterization that often relies on expensive physics-b

SEAL: Reinforcing Global Safety in Mixture-of-Experts through Shared Expert ALignment

arXiv:2609.02293v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) is a scaling architecture for large language models that activates only a small subset of expert modules per token, enabling

SkillGLoW: Procedural-Family Skill Consolidation for Self-Improving Agents on Long-Horizon Task Streams

arXiv:2609.02217v1 Announce Type: new Abstract: LLM agents increasingly self-improve by writing and reusing textual skills, kept either as one global document or as a flat pool of per-task entries, th

SocialBuddy: Tailoring Search Agent for Social Scenarios

arXiv:2609.01641v1 Announce Type: cross Abstract: In the era of digital social interaction, searching friends' posts from massive social streams has become a fundamental user need. However, while mode

SonicCaps: Large-Scale Diverse and Fine-Grained Captioning for Improved Audio-Retrieval

arXiv:2609.02343v1 Announce Type: cross Abstract: Recent advances in audio-language modeling have been driven by large-scale audio captioning datasets. However, existing datasets remain limited by low

researcharxiv-cs-cl

Source Distribution Estimation by Posterior Averaging

arXiv:2609.02622v1 Announce Type: new Abstract: Simulation-based science often requires a distribution over simulator parameters whose push-forward reproduces a set of real observations: this is the s

Spatially Aware World Action Model via Geometric Latent Diffusion

arXiv:2609.02531v1 Announce Type: new Abstract: World Action Models (WAMs) leverage the capabilities of large-scale pretrained video diffusion models to jointly predict future observations and actions

safetyarxiv-cs-cv

SpecXMaster Technical Report

arXiv:2603.23101v4 Announce Type: replace Abstract: Intelligent spectroscopy serves as a pivotal element in AI-driven closed-loop scientific discovery, functioning as the critical bridge between matte

safetyarxiv-cs-lg

Stepwise Think-Critique: Interleaved Reasoning and Self-Critique in a Single LLM

arXiv:2512.15662v4 Announce Type: replace Abstract: Human beings solve complex problems through critical thinking, where reasoning and evaluation are intertwined to converge toward correct solutions.

TAME: Temporal-Aware Mixture-of-Experts for Text-Video Retrieval

arXiv:2609.02204v1 Announce Type: new Abstract: Text-Video Retrieval (TVR) retrieves videos that match a natural-language query, but extending image-text models such as CLIP to videos is fundamentally

safetyarxiv-cs-cv

TempoGround: State-Aware Streaming Visual Grounding with Vision-Language Models

arXiv:2609.02359v1 Announce Type: new Abstract: Visual grounding maps language referents to spatial targets and is central to open-vocabulary perception with vision-language models. Existing methods h

researcharxiv-cs-cv

Ten Architectures, One Error: Shared Failure Modes in Hyperspectral Classification under Spatially Disjoint Evaluation

arXiv:2609.01786v1 Announce Type: new Abstract: Hyperspectral image classification still relies heavily on random pixel splits within a single scene. The Salinas dataset, randomly split, is among the

Applications

Test-Time Logit Prompting for Source-Free Missing Modality Adaptation

arXiv:2609.02039v1 Announce Type: new Abstract: Vision-language models (VLMs) have achieved remarkable performance by leveraging complementary information from large-scale image-text pairs. However, m

applicationsarxiv-cs-cv

Towards Effective Physical Reservoir Computing with a Pneumatic Soft Robot

model-releasesarxiv-cs-ro

arXiv:2609.02157v1 Announce Type: new Abstract: Physical reservoir computing (PRC) refers to the use of a physical dynamical system as a computational resource for tasks such as state estimation and c

Transfer Safety Awareness for Cross-Modal Safety Drift in Multimodal Large Language Models

arXiv:2609.02082v1 Announce Type: cross Abstract: Visual modality enhances the capabilities of multimodal large language models (MLLMs) but also introduces a safety concern: a benign textual query may

Local Ai

Uncertainty-Guided Adverse Weather Restoration via Gated Transformer Network

arXiv:2609.02434v1 Announce Type: new Abstract: Restoring images degraded by adverse weather remains challenging due to spatially heterogeneous degradations. Many existing weather-specific restoration

local-aiarxiv-cs-cv

Untangling the Mechanisms of Misleading Context in Medical Question Answering

arXiv:2609.02754v1 Announce Type: cross Abstract: Large language models now answer medical questions with expert-level performance. However, the context these systems act on can be misleading, and mis

Video-Based Palm-Vein Authentication under Challenging Conditions

arXiv:2609.02776v1 Announce Type: new Abstract: Palm-vein biometrics are increasingly used for secure, contactless authentication. Yet real-world deployment exposes them to surface noise (sweat, dirt)

Video Object Segmentation-Aware Audio Generation

arXiv:2509.26604v2 Announce Type: replace Abstract: Existing multimodal audio generation models often lack precise user control, which limits their applicability in professional Foley workflows. In pa

Video2Reaction: Training Foundation Video Models to Predict Audience Reaction

arXiv:2609.01816v1 Announce Type: new Abstract: We introduce Video2Reaction, a multimodal dataset that maps short movie segments to the induced emotional reactions of viewers in the wild, as expressed

Agents

When Evidence Shapes Collaboration: Knowledge-Conditioned Topology Generation for Multi-Agent Systems

arXiv:2608.27984v2 Announce Type: replace Abstract: Multi-Agent Systems (MAS) have recently moved from static workflows toward dynamically generated collaboration topologies. However, existing topolog

agentsarxiv-cs-ai

WinoQueer-NL: Assessing Bias in Dutch Language Models toward LGBTQ+ Identities

model-releasesarxiv-cs-cl

arXiv:2609.02651v1 Announce Type: new Abstract: While English language models have been widely examined for anti-queer bias, Dutch models remain understudied. To address this gap, we developed a cultu

ZETA: A Controlled Study of Zero-Shot Cross-Embodiment VLA Transfer for Tabletop Manipulation

model-releasesarxiv-cs-ro

arXiv:2609.02546v1 Announce Type: new Abstract: Zero-shot generalization to unseen embodiments is important for generalizable vision-language-action (VLA) models as robot hardware evolves and task-spe

A hybrid quantum-classical neural network for learning to route

arXiv:2609.00489v1 Announce Type: new Abstract: This work studies hybrid quantum-classical neural networks for learning routing heuristics. Specifically, this paper asks whether small quantum neural n

Applications

A Machine Learning-Driven Solution for Denoising Inertial Confinement Fusion Images

arXiv:2511.16717v3 Announce Type: replace-cross Abstract: Neutron imaging is essential for diagnosing and optimizing inertial confinement fusion implosions at the National Ignition Facility. Due to th

applicationsarxiv-cs-ai

A Multi-Branch Feature Fusion Approach for Health Misinformation Detection and Propagation

arXiv:2609.00403v1 Announce Type: new Abstract: This paper presents a multi-branch fusion framework for detecting and characterising the propagation of health misinformation in online social networks

A Text Recognition Dataset from Sahidic Coptic Ancient Manuscripts

arXiv:2606.15987v2 Announce Type: replace Abstract: In this work, we target Handwritten Text Recognition (HTR) in low-resource scenarios, which arise from underrepresented languages, rare scripts, and

Applications

Adaptive Critical Token-Aware Retrieval for Repository-Level Code Generation

arXiv:2609.01601v1 Announce Type: cross Abstract: The repository-level code generation task requires synthesizing code that satisfies task requirements while remaining consistent with the target repos

applicationsarxiv-cs-ai

Advantage Weighted Matching: Aligning RL with Pretraining in Diffusion Models

arXiv:2509.25050v2 Announce Type: replace Abstract: Reinforcement Learning (RL) has emerged as a central paradigm for advancing Large Language Models (LLMs), where both pre-training and RL post-traini

safetyarxiv-cs-lg