Search: “benchmark”

A Coulomb Particle Model for Learning Kernel Attention in Transformers

arXiv:2607.23869v1 Announce Type: cross Abstract: Randomized features provide a scalable approximation to kernel machines, but their performance depends strongly on the choice of feature distribution.

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A Few Words Go a Long Way: Language Guided Robot Policy Synthesis

DGX agent

arXiv:2607.23784v1 Announce Type: cross Abstract: While vision-language-action models have demonstrated impressive zero-shot manipulation capabilities, they remain fundamentally black box policies tha

model-releasesarxiv-cs-ai

28 Jul 2026

A Frozen 12B Beats Frontier Models on Verified Work: 100% Accuracy, 0 Tokens, Bit-Exact, Forever

arXiv:2607.23806v1 Announce Type: cross Abstract: Improving a language model today means retraining it: enormous compute, a new opaque model each cycle, non-deterministic output. We take the opposite

Act, Think or Abstain: Complexity-Aware Adaptive Inference for Vision-Language-Action Models

arXiv:2603.05147v2 Announce Type: replace Abstract: Current research on Vision-Language-Action (VLA) models predominantly focuses on enhancing generalization through reasoning techniques. While effect

researcharxiv-cs-cv

Adaptive Multi-Scale Forecasting and Gate-Localized Conformal Prediction for Multivariate Nonstationary Time Series

arXiv:2607.23165v1 Announce Type: cross Abstract: We propose ABF-T-GLCP, a model-agnostic framework for forecasting and uncertainty quantification in nonstationary multivariate time series. The centra

ADVERSARIAL: And-Inverter Graph-Assisted Hardware Trojan Detection At Scale

arXiv:2607.23882v1 Announce Type: new Abstract: Modern System-on-Chip (SoCs) often contain hundreds of millions to tens of billions of gates, making existing Hardware Trojan (HT) detection methods imp

researcharxiv-cs-lg

Agenta: an open-source Claude Cowork alternative where you can use self-hosted models (and any harness)

model-releasesr-localllama

Hey r/LocalLLaMA, I’m Mahmoud from Agenta. We built a self-hosted, more flexible, alternative to Claude Cowork . This short video shows how it works. I use it to build AI coworkers for my startup, lik

Agentic Permissions Policy Algebra for Taint Confinement in LLM Agents

arXiv:2607.24625v1 Announce Type: cross Abstract: Autonomous LLM agents processing mixed-confidentiality data face severe security risks from prompt injection attacks and reasoning errors. While dynam

Agentic Reward Modeling: Verifying GUI Agent via Progressive Trajectory-Grounded Interaction

arXiv:2602.00575v2 Announce Type: replace Abstract: Reinforcement learning with verifiable rewards (RLVR) provides a promising pathway for continuously advancing GUI agents, yet existing reward modeli

agentsarxiv-cs-ro

AIFL: A Global Daily Streamflow Forecasting Model Using a Deterministic LSTM Pre-trained on ERA5-Land and Fine-tuned on IFS

arXiv:2602.16579v2 Announce Type: replace-cross Abstract: Reliable global streamflow forecasting is essential for flood preparedness and water resource management, yet data-driven models often suffer

All in One: Generative Modeling as Mean-Field Game Design

arXiv:2607.23026v1 Announce Type: cross Abstract: Mean-field games (MFGs) offer a unifying lens on continuous-time generative modeling: a cost tuple recovering twelve prominent models---Continuous Nor

AlloBench: Measuring Online Tool Allocation Capability in LLM Agents

arXiv:2607.23332v1 Announce Type: new Abstract: Creating a reusable tool is an investment: an agent pays a fixed cost now in exchange for the potential of future reuse. Therefore, a user should prefer

An Agentic Orchestration of Atomistic Simulations

arXiv:2607.22596v1 Announce Type: new Abstract: Atomistic simulations are central to materials design, but their execution involves complex, multi-step workflows that require significant human experti

An Empirical Study of Feature Selection Granularity

arXiv:2607.24145v1 Announce Type: new Abstract: Feature selection aims to identify the most informative and relevant features for a given dataset, either in terms of capturing the underlying data stru

researcharxiv-cs-lg

ANSR-DT: A Neuro-Symbolic Framework for Adaptive and Explainable Digital Twins

arXiv:2501.08561v5 Announce Type: replace Abstract: Digital twins are increasingly used to monitor and optimize industrial systems, yet many existing frameworks remain difficult to interpret, slow to

Are Prompt Optimizers Blind? Cross-Modal Visual Feedback for Automatic Prompt Optimization

arXiv:2607.24354v1 Announce Type: new Abstract: Automatic prompt optimization (APO) has been widely adopted to adapt vision-language models (VLMs) to downstream tasks without weight updates, yielding

Asymmetric Hierarchical Anchoring for Robust Audio-Visual Cross-Modal Generalization

arXiv:2602.03570v2 Announce Type: replace Abstract: Audio-visual joint representation learning under Cross-Modal Generalization (CMG) aims to transfer knowledge from a labeled source modality to an un

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Auditing Alignment Controllability in LLMs via Political Axes

arXiv:2607.23519v1 Announce Type: cross Abstract: Political audits of large language models (LLMs) usually reduce each to one point on a political compass. But that resting point barely matters in dep

AutoMat: Enabling Automated Crystal Structure Reconstruction from Microscopy via Agentic Tool Use

arXiv:2505.12650v2 Announce Type: replace-cross Abstract: Reconstructing atomistic crystal structures from a single noisy STEM projection is an ill-posed inverse problem: multiple lattices can explain

Autoregressive One-Step Generative Modeling for Dynamical System Forecasting

arXiv:2605.05540v2 Announce Type: replace Abstract: Fast surrogate modeling for high-dimensional physical dynamics requires more than low short-term error: useful models must roll out efficiently whil

researcharxiv-cs-lg

BERT-based Models vs. Large Language Models for Low-Resource Named Entity Recognition: A Comparative Study on Marathi

arXiv:2607.23344v1 Announce Type: new Abstract: Named Entity Recognition (NER) for low-resource languages such as Marathi remains a challenging task due to limited annotated resources and linguistic c

Hardware

Beyond Block Boundaries: Multi-Block Editing for Diffusion Large Language Models

arXiv:2607.22663v1 Announce Type: new Abstract: Block diffusion has emerged as the dominant paradigm for scaling discrete diffusion language models (dLLMs), because decoding text in fixed-size blocks

hardwarearxiv-cs-ai

Beyond Scale and Generation: Understanding Language Model-based Entity Matching

arXiv:2607.24688v1 Announce Type: cross Abstract: Entity matching identifies records that refer to the same real-world entity. Language models can be adapted to this task through bi-encoder, cross-enc

Beyond Squared Error: Exploring Loss Design for Enhanced Training of Generative Flow Networks

arXiv:2410.02596v2 Announce Type: replace-cross Abstract: Generative Flow Networks (GFlowNets) are a novel class of generative models designed to sample from unnormalized distributions and have found

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Beyond Success Rate: Cost-Aware Evaluation of Offensive and Defensive Security Agents

arXiv:2607.15263v3 Announce Type: replace-cross Abstract: Security-agent evaluations commonly measure peak offensive capability under generous inference budgets, emphasizing vulnerability discovery, e

Tutorials

BeyondFusion: Self-Aligned Latent Diffusion for Calibration-Free Infrared Super-Resolution and Infrared-Visible Fusion

arXiv:2607.24110v1 Announce Type: new Abstract: Mobile infrared-visible imaging typically pairs a compact infrared sensor with a high-resolution visible camera for complementary perception. While cros

tutorialsarxiv-cs-cv

BHARATI: Morphology-Aware Tokenizers for Classical Indian Languages with Subword Fertility Analysis

arXiv:2607.23319v1 Announce Type: new Abstract: Standard subword tokenization algorithms such as Byte-Pair Encoding (BPE) and SentencePiece are trained predominantly on modern language corpora and pro

Local Ai

CADER: Confidence-Aware Dynamic Evidence Reasoning for Long-Video Understanding

arXiv:2607.24582v1 Announce Type: cross Abstract: Long-video understanding increasingly relies on large vision-language models and tool-augmented reasoning, but most systems apply the same inference p

local-aiarxiv-cs-ai

CALMRec: Causally Aligned Language Memory for Long-Horizon Recommendation

arXiv:2607.23647v1 Announce Type: cross Abstract: Large language models (LLMs) can summarize heterogeneous user evidence in natural language, but current LLM recommenders often collapse enduring prefe

Can Context Bridge the Reality Gap? Sim-to-Real Transfer of Context-Aware Policies

model-releasesarxiv-cs-ro

arXiv:2511.04249v2 Announce Type: replace Abstract: Sim-to-real transfer remains a major challenge in reinforcement learning (RL) for robotics, as policies trained in simulation often fail to generali

CausalGate: Causal Importance Distillation for Transformer Module Pruning

arXiv:2607.22720v1 Announce Type: cross Abstract: Existing adaptive inference methods for Large Language Models rely on observational heuristics, such as hidden-state similarity or activation magnitud

CC-AOS: Cost- and Horizon-Conditioned Amortized Backward Induction for Finite-Horizon Optimal Stopping

arXiv:2607.22774v1 Announce Type: new Abstract: Finite-horizon optimal stopping is a central problem in early time-series classification, where a system must decide at each sequence prefix whether the

Chamaileon: Cross-Context Binder Design with Contextualized Modeling and Mixed Sampling

arXiv:2607.23518v1 Announce Type: new Abstract: The rapid evolution of generative models has unlocked new potentials in protein binder design, a pivotal task in structural biology, by facilitating end

Co-Evolving Graph and Text Memory for Training-Free Multi-Hop Question Answering

arXiv:2607.23278v1 Announce Type: new Abstract: Multi-hop question answering requires coordinating relational and textual evidence across reasoning steps, a combination neither a text corpus nor a kno

researcharxiv-cs-cl

Applications

Co-Learning for Missing Arbitrary Modalities in Multi-modal Classification

arXiv:2607.24683v1 Announce Type: cross Abstract: Multi-modal classification leverages complementary information across diverse data sources to enhance predictive performance. However, real-world scen

applicationsarxiv-cs-ai

CodeEvo: Interaction-Driven Synthesis of Code-centric Data through Hybrid and Iterative Feedback

arXiv:2507.22080v2 Announce Type: replace-cross Abstract: Acquiring high-quality instruction-code pairs is essential for training Large Language Models for code generation. While automated synthesis h

CodexGraph: Bridging Large Language Models and Code Repositories via Code Graph Databases

arXiv:2408.03910v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) excel in stand-alone code tasks like HumanEval and MBPP, but struggle with handling entire code repositories. Thi

Compiler-Grounded Hierarchical Diagnosis for LLM-Based Triton Kernel Optimization

arXiv:2607.23089v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have enabled automated kernel generation and optimization, but most existing approaches rely on surface

Concept-based Visual Counterfactual Explanations with Diffusion Models

arXiv:2607.22544v1 Announce Type: new Abstract: Visual counterfactual explanations aim to answer 'what minimal change to this image would flip the model's prediction?', and are increasingly important

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Confidently Wrong: Exception Chain Collapse in Frontier LLM Rule Evaluation

arXiv:2607.23386v1 Announce Type: new Abstract: We document a failure class in frontier large language models -- exception chain collapse -- observed in eligibility evaluation under nested conditional

Continual Knowledge Consolidation LORA for Domain Incremental Learning

arXiv:2510.16077v2 Announce Type: replace-cross Abstract: Domain Incremental Learning (DIL) is a sub-branch of continual learning that aims to address the never-ending arrival of new domains without c

CuraWeb: Joint Optimization of Quality, Redundancy, and Diversity for Web-Scale Pretraining Data

arXiv:2607.22662v1 Announce Type: new Abstract: Open-web corpora curated via highly selective filters, such as FineWeb-Edu and DCLM, constitute the core of LLM pretraining data and have significantly

DAP-Pose: Deep Temporal Alignment and Physics-aware Cross-modal Sensor Fusion for Robust Pose Estimation

model-releasesarxiv-cs-cv

arXiv:2607.23755v1 Announce Type: new Abstract: Robust and accurate pose estimation with multi-modal sensors is fundamental for autonomous vehicles and mobile robotic systems in complex environments.

DataOrchestra: Learning to Orchestrate Per-Example Curation of Pretraining Data

arXiv:2607.24717v1 Announce Type: cross Abstract: Pretraining data processing is critical to the downstream performance of Large Language Models (LLMs). However, many existing approaches define a fixe

DDVT: Dynamic Dual-level Vision Transformer Fusion Network for Answer Grounding in Visual Question Answering

arXiv:2607.23921v1 Announce Type: new Abstract: Answer grounding in visual question answering aims to locate the region from a given natural language question associated with the visual content of an

researcharxiv-cs-cv

DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding

arXiv:2607.24554v1 Announce Type: cross Abstract: Advancing multimodal retrieval-augmented generation (RAG) for complex document understanding presents a formidable dual dilemma of accuracy and effici

researcharxiv-cs-cv

DeepLook: Deeper Thinking with Lookahead

arXiv:2607.22602v1 Announce Type: new Abstract: Inference-time scaling has emerged as a powerful paradigm for improving large language model reasoning, often delivering larger gains on difficult reaso

DeVA: Decoupled Video-Action Model with physical guidance for robot policy learning

arXiv:2607.24159v1 Announce Type: cross Abstract: Generalizable robot manipulation requires policies that can anticipate how visual scenes evolve while executing language instructions. While recent Vi

safetyarxiv-cs-cv