Search: “benchmark”

Semantic Reasoning Denoising: Correcting Language Model Reasoning with Semantic Operators

arXiv:2608.22090v1 Announce Type: cross Abstract: Large language models can produce fluent reasoning traces whose local semantic errors propagate to an incorrect conclusion, while unconstrained self-c

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Model Releases

SkillBloat: Token Amplification Attacks via Skill Injection in LLM Coding Agents

DGX agent

arXiv:2608.21929v1 Announce Type: cross Abstract: Agent skills extend coding agents with task-specific instructions, scripts, and resources, but they also create a trusted instruction channel that can

model-releasesarxiv-cs-cl

25 Aug 2026

SlideGen: Collaborative Multimodal Agents for Scientific Slide Generation

arXiv:2512.04529v3 Announce Type: replace Abstract: Creating presentation slides from scientific papers is not simply a matter of summarizing paragraphs. A presenter is required to decide what story t

SLogic: Subgraph-Informed Logical Rule Learning for Knowledge Graph Completion

arXiv:2510.00279v3 Announce Type: replace-cross Abstract: Logical rule-based methods offer an interpretable approach to knowledge graph completion (KGC) by capturing compositional relationships in the

SlotMem: Character-Addressable Internal Memory for Narrative Long Video Generation

arXiv:2607.15772v2 Announce Type: replace Abstract: Maintaining recurring character identities across scene transitions and long temporal gaps is a central challenge in narrative long video generation

Software Frameworks for Explainable AI in Time Series Classification: A Systematic Review

arXiv:2608.21449v1 Announce Type: new Abstract: Time series arise in a wide range of application domains and are analyzed using machine learning in decision-critical settings. Time series classificati

researcharxiv-cs-ai

Spicing up Genetic Netlist Generation with LLMs

model-releasesarxiv-cs-lg

arXiv:2608.23317v1 Announce Type: cross Abstract: Analog circuit topology synthesis remains challenging because useful designs occupy a tiny fraction of a combinatorial search space, and small structu

Agents

Spiking Neural Networks for Energy-Efficient Object Detection in Forward-Looking Sonar Imagery

arXiv:2608.22072v1 Announce Type: new Abstract: Autonomous underwater vehicles (AUVs) are increasingly important tools in industries ranging from research, to energy, to defense. AUVs are power-constr

agentsarxiv-cs-cv

SplitLite: Low-Rank Residual Compression for Split Learning

arXiv:2608.23018v1 Announce Type: cross Abstract: Federated fine-tuning of on-device large language models (LLMs) faces a significant computing burden. To overcome this limitation, split learning (SL)

Spotter: Efficient Urban Visual Localization via Geo-Referenced Facade Landmarks in GPS-Degraded Environments

arXiv:2608.23290v1 Announce Type: new Abstract: Accurate visual localization on robotic and wearable platforms remains challenging in dense urban environments. Existing methodologies typically rely on

Spyre-Accelerated Retrieval-Augmented Generation on IBM LinuxONE: A Cloud-Native Architecture for Secure, High-Throughput Enterprise AI Inference

arXiv:2608.21393v1 Announce Type: new Abstract: Running large language models inside enterprise environments has always bumped up against a practical wall: the data lives in one place, the AI horsepow

SRPO: Self-Reflective Policy Optimization for Long-Horizon Reasoning

arXiv:2608.23493v1 Announce Type: new Abstract: Self-reflection is a powerful mechanism for credit assignment in human learning, converting sparse outcome feedback into actionable guidance. However, i

safetyarxiv-cs-ai

SSE-Bio: A Structured Self-Evolving Agent with Agentic Retrieval Policy for Multi-Hop Biomedical Reasoning

arXiv:2608.22132v1 Announce Type: cross Abstract: Biomedical multi-hop question answering (QA) requires models to connect evidence across intermediate entities such as diseases, drugs, proteins, and p

safetyarxiv-cs-ai

Agents

ST-EVO: Towards Generative Spatio-Temporal Evolution of Multi-Agent Communication Topologies

arXiv:2602.14681v4 Announce Type: replace-cross Abstract: LLM-powered Multi-Agent Systems (MAS) have emerged as an effective approach towards collaborative intelligence, and have attracted wide resear

agentsarxiv-cs-ai

ST^2U: Stateful Test-Time Unlearning via Restricted Knowledge Boundary Control

arXiv:2608.23034v1 Announce Type: cross Abstract: Controlling restricted knowledge in large language models is essential for model alignment and safe deployment. Test-time unlearning avoids costly ret

STAGE: Stateful Translation to Agentic Graph Execution with Policy-Scoped Context and Deterministic Control

arXiv:2608.22538v1 Announce Type: new Abstract: Policy-governed agents must interpret case evidence while following an authorized procedure. We present extsc{Stage}, an executable-graph framework that

Statistical Machine Translation Systems of English-Pnar Language Pair : Some Insights of the Emperical Study

arXiv:2608.23120v1 Announce Type: cross Abstract: Pnar, an Austroasiatic language spoken by approximately 0.4 million people in the Jaintia Hills of Meghalaya, lacks the digital corpora and natural la

Applications

StereoDiff: Stereo-Diffusion Synergy for Video Depth Estimation

arXiv:2506.20756v4 Announce Type: replace Abstract: Recent video depth estimation methods achieve great performance by following the paradigm of image depth estimation, i.e., typically fine-tuning pre

applicationsarxiv-cs-cv

StereoDiffuer: Diffusion-based Progressive Geometry Modeling with Saliency Attention Perception for Stereo Matching

arXiv:2608.21710v1 Announce Type: new Abstract: With the advance of deep neural networks, the quality of disparity maps obtained through stereo matching has steadily improved. However, existing stereo

StrategyBench: Evaluating Explicit Strategy Induction in Large Language Models

arXiv:2608.23475v1 Announce Type: new Abstract: As large language models are increasingly used in data-scarce and evolving task scenarios, few-shot in-context learning (ICL) has become a key paradigm

SuperMap: A Spatio-Temporal SLAM System for Visual-Language Navigation

arXiv:2608.22896v1 Announce Type: new Abstract: Robotic navigation in human environments requires a spatio-temporal semantic representation that can rec- oncile open-vocabulary perception with long-te

researcharxiv-cs-ro

Sycophants in the Courtroom: Are LLMs Fragile to Juridical Authority and Evolving Legal Standards?

arXiv:2608.21409v1 Announce Type: cross Abstract: In medicine, claims remain valid when supported by empirical evidence grounded in stable biological reality. In law, by contrast, truth is contingent,

Task-Driven 3D Printability Assistance via Geometry- and Knowledge-Grounded LLM Reasoning

arXiv:2608.22128v1 Announce Type: new Abstract: Printability assessment in additive manufacturing is typically conducted at the geometry level before printing to determine whether a computer-aided des

TASSO: TAsk-Specific Subspace Optimization for Continual Learning of Vision-Language Models

arXiv:2608.21487v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) exhibit strong zero-shot capabilities, making them an attractive solution for continual learning across diverse tasks. H

Tutorials

Teaching LLMs How ICU Physicians Approach Clinical Reasoning Through OMOP-Aligned Retrieval Improves Reasoning Across Clinical Domains

arXiv:2608.22622v1 Announce Type: cross Abstract: Clinical decision-making relies on identifying relevant patient information to guide diagnosis and treatment, a challenge that is especially difficult

tutorialsarxiv-cs-ai

Text-Guided Visual Dependency Graph Learning with Cross-Modal Attention Priors

arXiv:2608.21443v1 Announce Type: new Abstract: Estimating interpretable conditional-dependence structures from multimodal visual-linguistic features remains largely unexplored. We propose CM-GLasso (

The Chase Is the Curriculum, the Capture Anchors the Credit: Pursuit-Evasion Self-Play for Zero-Data LLM Reasoning

arXiv:2608.21871v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards has become the dominant recipe for improving large language model reasoning, yet it presumes large human-

researcharxiv-cs-cl

The Compaction Cliff in Long-Running AI Agent Memory

arXiv:2608.22752v1 Announce Type: new Abstract: A safety rule and an episodic log compete for the same tokens in an AI agent's context. When the budget overflows, both are summarized at the same rate;

Applications

The Illusion of Control: Why Bare Classifier Inversion Silently Fails in Concept-Bottleneck Text Generation

arXiv:2608.22956v1 Announce Type: new Abstract: Concept-bottleneck controllable generation routes multi-attribute control through a low-dimensional concept code that, at deployment, must be synthesise

applicationsarxiv-cs-cl

Thinking Beyond Videos: Unifying Video Reasoning and Deep Research for Open-World Video Agents

arXiv:2608.23329v1 Announce Type: cross Abstract: Open-world video understanding often requires a model to locate sparse visual evidence and acquire external knowledge that is absent from the video an

TO-Agents: A Multi-Agent AI Framework for Subjective Preference-Guided Topology Optimization

arXiv:2605.21622v2 Announce Type: replace Abstract: Topology optimization can generate efficient structures, but designers often must manually translate qualitative intent, such as desired visual styl

Tomatoes, Potatoes, and Onions: Questioning the Need for Faces in Face Presentation Attack Detection

arXiv:2608.21455v1 Announce Type: new Abstract: Face presentation attack detection (PAD) is traditionally formulated as a face-specific problem, although many of the visual artifacts introduced by pri

TRACE: Temporal Retrieval with Anchored and Convergent Evidence for Long-Horizon Video Understanding

arXiv:2608.22516v1 Announce Type: cross Abstract: A long-video answer is evidence-supported only when the frames decoded from the video cover every event the answer depends on. Existing evaluations sc

Training-Free Pseudo-Fusion for Composed Image Retrieval with Diffusion Models and Multimodal Large Language Models

arXiv:2608.23102v1 Announce Type: new Abstract: Composed Image Retrieval (CIR) is an emerging paradigm in content-based image retrieval that enables users to formulate compositional queries by combini

TSWAP: A Multilingual Retrieval-Augmented Thai Wellness Advisor

arXiv:2608.22917v1 Announce Type: new Abstract: We present TSWAP, a deployed eight-language conversational wellness advisor grounded, via retrieval-augmented generation, in a verified knowledge base o

Local Ai

Unlearning Is Not Just Erasing: Temporal Decoupling via Generation Inequality

arXiv:2608.23020v1 Announce Type: cross Abstract: Large language models (LLMs) require effective unlearning to address privacy regulations and safety concerns. However, achieving precise forgetting wi

local-aiarxiv-cs-ai

Unveiling the Depth-Performance Dilemma in Split-Federated Fine-tuning of LLMs

arXiv:2608.22188v1 Announce Type: cross Abstract: Split Federated Fine-tuning (SFF) is a promising paradigm for scaling Large Language Models (LLMs) by partitioning model depth between resource-constr

VERDICT: Agreement Beats Pixel-Space Verification in Real-Document OCSR

arXiv:2608.22183v1 Announce Type: new Abstract: Optical Chemical Structure Recognition (OCSR) converts 2D molecular depictions in the published literature into SMILES, and is increasingly important fo

Vibe Coding on Trial: Operating Characteristics of Unanimous LLM Juries

arXiv:2602.18492v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are now good enough at coding that developers can describe intent in plain language and let the tool produce the

VideoChat3: Fully Open Video MLLM for Efficient and Generalist Video Understanding

arXiv:2607.14935v2 Announce Type: replace Abstract: Recent advances in video understanding have spanned motion, long video, and streaming interaction, driving this field toward real-world applications

VIG: Visual Information Gain as a Reward Signal for Multimodal Chain-of-Thought Compression

arXiv:2608.21883v1 Announce Type: new Abstract: Multimodal large reasoning models often rely on long Chain-of-Thought (CoT) traces in which a substantial fraction of tokens, such as repeated visual de

safetyarxiv-cs-cv

VinciCoder: Unifying Multimodal Code Generation via Coarse-to-fine Visual Reinforcement Learning

arXiv:2511.00391v3 Announce Type: replace Abstract: While recent specialized multimodal code generation models excel in tasks like chart-to-code generation, their reliance on single-task training limi

safetyarxiv-cs-cv

Vision Guided Target Conditioned Control for Autonomous Excavation

model-releasesarxiv-cs-ro

arXiv:2608.21778v1 Announce Type: new Abstract: Autonomous excavation requires an intelligent control system that can convert spatial work intent into coordinated bucket motion under contact-rich soil

VisionCoach: Reinforcing Grounded Video Reasoning via Visual-Perception Prompting

arXiv:2603.14659v2 Announce Type: replace-cross Abstract: Video reasoning requires models to locate and track question-relevant evidence across frames. While reinforcement learning (RL) with verifiabl

researcharxiv-cs-ai

VISTA: Test-Time Compositional Alignment for Visual Autoregressive Generation

arXiv:2608.22521v1 Announce Type: new Abstract: Visual autoregressive (VAR) models have emerged as a fast, high-quality alternative to diffusion for text-to-image generation, but like diffusion models

safetyarxiv-cs-cv

Agents

When Not to Imitate: Boundary-Aware Skill Memory for Reliable Tool-Use LLM Agents

arXiv:2608.22339v1 Announce Type: new Abstract: Extracting skills from past successes is critical for the efficient evolution of Large Language Model (LLM) agents. Prevailing agent self-evolution para

agentsarxiv-cs-cl

When Persona Simulations Are Informative: Graph-Structured Signals for Pluralistic Opinion Sensing

arXiv:2608.22438v1 Announce Type: new Abstract: Persona-conditioned large language models (LLMs) are increasingly used to simulate survey responses across diverse domains. However, apparent response v

researcharxiv-cs-ai

When Test-Time Adaptation Helps, Harms, or Becomes Inactive: A Condition-Level Study on CIFAR-10-C

arXiv:2608.22233v1 Announce Type: cross Abstract: Test-time adaptation (TTA) aims to improve model robustness under distribution shift by adapting a source model using unlabeled test data. Although me