Search: “benchmark”

Subgraph Filtering for Fair Graph Neural Networks

arXiv:2608.26437v1 Announce Type: new Abstract: Graph neural networks (GNNs) can exhibit unfair behavior even when sensitive attributes are excluded from node features, because graph topology and mess

Subspace Alignment for Vision-Language Model Test-time Adaptation

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DGX agent

arXiv:2601.08139v2 Announce Type: replace-cross Abstract: Vision-language models (VLMs), despite their extraordinary zero-shot capabilities, are vulnerable to distribution shifts. Test-time adaptation

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28 Aug 2026

Survival-Guided Length Control for Efficient Diffusion Language Models

arXiv:2608.26374v1 Announce Type: new Abstract: Diffusion language models (DLMs) generate text by iteratively denoising masked sequences, but standard decoding either fixes the sequence length or reli

SymbolLKG: Towards Verifiable Logical Reasoning via Logical Knowledge Graph and Symbolic Solvers

arXiv:2608.26836v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable proficiency in natural language understanding, yet they struggle with strict multi-step reason

researcharxiv-cs-ai

TabuLM: Morphology-Aware Tabular Pre-training for Low-Resource Languages

arXiv:2608.26923v1 Announce Type: new Abstract: We present TabuLM, the first language model pre-trained on Kinyarwanda tabular data. Kinyarwanda is a morphologically rich Bantu language spoken by over

TADP: Task-Aware Deformable Prediction for Single-Stage 3D Object Detection

model-releasesarxiv-cs-ai

arXiv:2608.27282v1 Announce Type: cross Abstract: Most single-stage 3D object detectors complete different tasks with the same extracted features. Nevertheless, it is impossible to project features in

TelecomGPT-R1: A Unified Open-Source Reasoner for the Telecom Stack

arXiv:2608.26126v1 Announce Type: new Abstract: Telecommunications is a high-leverage domain for large language model (LLM)-based reasoning because routine engineering workflows require joint groundin

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Temporal Sensitivity Analysis of Tessera Embeddings

arXiv:2608.27175v1 Announce Type: new Abstract: Many Earth Observation applications need land-use/land-cover maps that are both precise and frequently updated, yet the strongest Earth Observation foun

Text-to-seed generation: Training-free open-vocabulary seeded semantic segmentation via re-purposing diffusion as text-guided seed generator

arXiv:2608.26624v1 Announce Type: new Abstract: Open-vocabulary semantic segmentation (OVSS) aims to segment image regions corresponding to arbitrary text queries. Although the Segment Anything Model

The Score Granularity Gap in Black-Box LLM Classification: A Comparative Study of Confidence Constructions

arXiv:2606.22179v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly deployed as black-box classifiers in pipelines that automate confident decisions and route uncertain o

Today I hit 181 toks/s (aggregate) on Qwen3.8-Flash-Next on 2x DGX Sparks

model-releasesr-localllama

Hey all, and hello fellow DGX Spark-ers! Today I managed some pretty crazy numbers: 181 tok/s aggregate on 2× DGX Spark on Qwen3.8-Flash-Next at 512Kcontext (2.8M kvc) I hit 181 tok/s aggregate today

TontaubeV1 - Open TTS model release for local long-form generation

model-releasesr-localllama

Hey everyone, I am the co-founder of Tontaube. My brother and I just released TontaubeV1, a 2.9B-parameter open-weight TTS model focused on expressive speech, long-form generation, and low-latency loc

TopiCLEAR: Adaptive embedding clustering for interpretable topic discovery from short texts

arXiv:2512.06694v2 Announce Type: replace Abstract: Topic discovery is a fundamental technique for text mining that identifies abstract topics within large document collections. A recent approach to t

TQwen 3.8 flash next ud1s on 6gb vram and 16 gb system ram

model-releasesr-localllama

After getting tired refreshing and searching sub reddits for qwen 3.8 35 a3b i decided to give qwen 3.8 flash next a try . So I dual booted and built llama cpp I am able to hit 6-7 tps constantly insi

TreeGraft: Adaptive Multi-Drafter Grafting for Tree-Based Speculative Decoding

arXiv:2608.26112v1 Announce Type: new Abstract: Speculative decoding accelerates large language model inference through a draft-then-verify paradigm. Building on this, tree-structured methods improve

TTPO: Test-Time Policy Optimization

arXiv:2608.27448v1 Announce Type: new Abstract: Recent prominent post-training methods, such as Reinforcement Learning (RL) and On-Policy Self-Distillation (OPSD), have driven rapid progress in mathem

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Agents

Verify Smarter, Evolve Further: Efficient Harness Evolution through Behavior-Aware Verification

arXiv:2608.27311v1 Announce Type: new Abstract: Agent harnesses shape how language-model agents use instructions, tools, and runtime components, but adapting these harnesses requires costly verificati

agentsarxiv-cs-ai

VFA: Empowering Multilingual MLLMs via Vision-Free Adaptation

arXiv:2608.26155v1 Announce Type: cross Abstract: Multimodal large language models have advanced rapidly, yet most remain English-centric, as scaling multilingual multimodal instruction tuning is limi

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Video-OPSD: Exploiting Privileged Visual Evidence for On-Policy Self-Distillation in Video Large Language Models

arXiv:2608.27065v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) has recently emerged as an effective post-training paradigm that improves policy optimization through dense token-lev

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When Memory Takes Gradients: Collaborative Vector Memory for Agentic Recommender Systems

arXiv:2608.26895v1 Announce Type: cross Abstract: Agentic recommender systems ground each decision of a large language model (LLM) in a persistent memory of the user, and in existing agents that memor

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Who Remains, What Changes: Identity Anchored Composed Gait Retrieval

arXiv:2608.26632v1 Announce Type: new Abstract: Gait recognition has achieved remarkable progress, yet existing methods remain confined to rigid visual matching and often overlook the potential of nat

Zero-Shot Self-Orchestration with Ledger-Based Control for Improved LLM Coding Performance

model-releasesarxiv-cs-ai

arXiv:2608.26480v1 Announce Type: cross Abstract: Multi-agent large language model systems are widely reported to beat single-model baselines, but the evidence is mixed, and comparisons are usually co

A Hierarchical Synergistic Deep Learning Framework Integrating Composition, Structure, and Ionic Transport for Solid-State Electrolyte Discovery

arXiv:2608.25592v1 Announce Type: cross Abstract: Inorganic solid-state electrolytes must combine high room-temperature ionic conductivity, a wide electrochemical window, excellent electronic insulati

researcharxiv-cs-lg

A Token-Level Analysis of Sampled-Token Reverse-KL On-Policy Distillation

arXiv:2608.25643v1 Announce Type: cross Abstract: On-policy distillation (OPD) supervises a student on its own trajectories with token-level signals from a frozen teacher, yet how a sampled loss alloc

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AdaptiveEmbed: Sample-Adaptive Multi-Vector Representation for Multimodal Retrieval

arXiv:2608.25412v1 Announce Type: new Abstract: Multi-vector representations have emerged as an effective paradigm for multimodal retrieval, representing each sample with multiple complementary embedd

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AdaVDR: Adaptive Tool Use and Reflection for Video Deep Research

model-releasesarxiv-cs-cv

arXiv:2608.25559v1 Announce Type: new Abstract: Video deep research answers complex questions by jointly understanding video content and retrieving external knowledge from the open Web. However, diver

Applications

Addressing the Reasoning Gap: Mechanistic Circuit-Based Knowledge Editing in Large Language Models

arXiv:2604.05876v2 Announce Type: replace Abstract: Deploying Large Language Models (LLMs) in real-world dynamic environments raises the challenge of updating their pre-trained knowledge. While existi

applicationsarxiv-cs-cl

AFDBench: A Reasoning-First AI Scientist for NationalWeather Service Forecast Discussions

arXiv:2608.24954v1 Announce Type: new Abstract: Large language models (LLMs) hallucinate numerical values when generating high-stakes meteorological text, posing risks for weather communication. We pr

AlgoTrace: Algorithmic Primitives and Compositional Geometry of Reasoning in Language Models

arXiv:2510.15987v3 Announce Type: replace Abstract: How do inference time and latent computations enable large language models (LLMs) to solve multi-step reasoning problems? We introduce AlgoTrace, a

Anytime Global Tensor Motion Planning

arXiv:2608.25830v1 Announce Type: new Abstract: Global Tensor Motion Planning (GTMP) solves motion planning with batched tensor operations over a layered multipartite graph. We generalize GTMP so that

researcharxiv-cs-ro

Agents

AsymSpec: Context-Asymmetric Speculative Decoding for Agentic LLMs

arXiv:2608.26004v1 Announce Type: cross Abstract: Agentic LLM pipelines face escalating inference costs as context accumulates across retrieval, tool use, and multi-turn interactions. To control laten

agentsarxiv-cs-cl

Automatic weld seam segmentation for industrial quality control: a comparison of RGB and polarimetric imaging with CNN and transformer architectures

arXiv:2608.25465v1 Announce Type: new Abstract: Visual inspection of welded assemblies remains one of the least automated stages in many industrial production processes, still depending largely on the

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AutoVerifier: Residual-Guided Non-Parametric Optimization for Reference-Based Answer Verification

arXiv:2608.25637v1 Announce Type: new Abstract: Reference-based verifiers are important for evaluating reasoning models and providing accurate outcome rewards in reinforcement learning with verifiable

Ban&Pick: Enhancing Performance and Efficiency of MoE-LLMs via Smarter Routing

arXiv:2509.06346v3 Announce Type: replace Abstract: Sparse Mixture-of-Experts (MoE) has become a key architecture for scaling large language models (LLMs) efficiently. Recent fine-grained MoE designs

Beam Search, Self-Consistency, and the Limits of Inference-Time Scaling for Grammar-Constrained Text-to-SQL in Small Language Models

arXiv:2608.25761v1 Announce Type: new Abstract: One common trade-off in the use of large language models involves reducing the size of the model while increasing the amount of computation at inference

Beyond Tokens: Probing Higher-Order Epistasis in Learned Protein Representations

arXiv:2608.24953v1 Announce Type: cross Abstract: Protein fitness landscapes contain nonlinear interactions in which mutation effects depend on other residues. We introduce ORBIT, an Order-Resolved Be

researcharxiv-cs-lg

BRIDLE: Generalized Self-supervised Learning with Quantization

arXiv:2502.02118v2 Announce Type: replace-cross Abstract: Self-supervised learning has been a powerful approach for learning meaningful representations from unlabeled data across various domains, redu

Can We Read the Mind of an Audio LLM? A Verbalizable, Multilingual Middle-Layer Workspace

arXiv:2608.24958v1 Announce Type: cross Abstract: An audio language model is a black box in a specific way: we see what it says, never what it works out on the way there, and chain-of-thought monitori

Local Ai

CloSeR: Unified Relational Distillation from Closed-Set Teachers for Category Discovery

arXiv:2608.25692v1 Announce Type: new Abstract: Generalized Category Discovery (GCD) is an intriguing open-world problem that has garnered increasing attention: given partially labelled data, the goal

local-aiarxiv-cs-cv

CoRE: Weakly Supervised Coarse-to-Fine Risk Evidence Learning in Driving Videos

model-releasesarxiv-cs-cv

arXiv:2608.25344v1 Announce Type: new Abstract: Perceived risk in driving evolves over time and may be supported by specific scene entities, yet supervision is typically limited to coarse video-level

CRAMER: Control via Request-Aware Masking for Editing Recommenders

arXiv:2608.25370v1 Announce Type: cross Abstract: Sequential recommendation models, while powerful, have limited flexibility in responding to immediate user requests, making it difficult to adapt thei

D^3-MOPD: Adaptive Dynamic Domain ScheDuling for Efficient Multi-Teacher Distillation

arXiv:2608.24987v1 Announce Type: new Abstract: Multi-teacher on-policy distillation (MOPD) distills several domain-expert teachers into a single student by minimizing per-domain reverse-KL divergence

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Hardware

DataKernelBench: Can LLMs Optimize Database Queries on GPUs?

arXiv:2608.25061v1 Announce Type: new Abstract: GPUs increasingly accelerate database systems, but query-specific peak performance still often relies on hand-written kernels. Existing LLM kernel bench

hardwarearxiv-cs-cl

DCGC: Draft-Conditioned Global Correction for Complex Reasoning with Masked Diffusion Models

arXiv:2608.25428v1 Announce Type: new Abstract: Correcting flawed reasoning traces remains a significant challenge for Large Language Models (LLMs), whose autoregressive generation can propagate early

Local Ai

Deep Learning Segmentation of Diffusion-Weighted MRI Acute Ischaemic Stroke: A Pragmatic Evaluation Across Three Datasets

arXiv:2608.25675v1 Announce Type: new Abstract: Objective: Diffusion-weighted MRI (DWI-MRI) is the gold standard for visualizing and quantifying acute ischaemic stroke (AIS). Although deep learning me

local-aiarxiv-cs-cv

DESCENT: Directed Edge Scene Encoding for Airport Surface Movement Prediction

model-releasesarxiv-cs-ro

arXiv:2608.26002v1 Announce Type: new Abstract: Advanced automation is a key technology for enhancing the safety of ground operations amidst the increasing density of commercial air traffic. While mot

Drift Variation Autoencoder: Unifying Generation and Representation Learning through Conditional Posterior Flow Matching

arXiv:2608.25138v1 Announce Type: new Abstract: Stochastic masking, cropping, or modality removal makes deterministic reconstruction an incomplete target: one observation can admit many clean completi

E2Rank: Unifying Text Embedding and Listwise Reranking for Effective and Efficient Search

arXiv:2510.22733v3 Announce Type: replace Abstract: Text embedding models deliver competitive retrieval performance with high efficiency, but their ranking fidelity remains limited compared to LLM-bas