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SemiAdapt-Instruct: Extensible Instruction Tuning via Latent Domain-Specialised Adapters

model-releasesarxiv-cs-cl

arXiv:2608.05161v1 Announce Type: new Abstract: Instruction-tuned LLMs are deployed into environments where domains evolve, yet extending a fine-tuned model's capabilities without full retraining rema

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Research

Shape-Aware Oriented Bounding Box (OBB) to Horizontal Bounding Box (HBB) Conversion

DGX agent

arXiv:2608.05858v1 Announce Type: new Abstract: Accurate object detection in aerial and satellite imagery is dependent upon the bounding box representation. This is especially true for spatially orien

researcharxiv-cs-cv

7 Aug 2026

Shapes from Examples: Foundations of Shape Learning in Recursive SHACL

arXiv:2607.27934v2 Announce Type: replace Abstract: SHACL shapes enable data graph validation, making automatic shape learning essential for knowledge graph applications. We investigate the well-known

Shaping Human-AI Interactions to Provide Improvement Pathways and Balance Competing Objectives

arXiv:2608.05710v1 Announce Type: new Abstract: When an AI system is deployed, the individuals who use and or are evaluated by it form beliefs about how the system operates and use those beliefs to st

tutorialsarxiv-cs-ai

Shrinking the Generation-Verification Gap with Weak Verifiers

model-releasesarxiv-cs-cl

arXiv:2506.18203v3 Announce Type: replace Abstract: Verifiers can improve language model capabilities by scoring and ranking responses from generated candidates. Currently, high-quality verifiers are

Signal or Spurious Cue? A Randomized Audit of Survey-Country Metadata in LLM Social Inference

arXiv:2608.06085v1 Announce Type: new Abstract: Survey-country metadata can improve an LLM's forecast of an individual response when informative, yet the same cue may redirect the forecast when assign

Simulator-Grounded Large Language Models for Industrial Causal Reasoning: Tool-Use, Structured Injection, and Plant-Portable Retrieval for Wastewater Treatment Decision Support

arXiv:2608.05151v1 Announce Type: cross Abstract: Wastewater operators need answers grounded in how their plant's variables interact and how fast effects propagate, not in generic pretraining text, wh

SkillHEX: Improving Agent Skills via Hypothesis-Driven Autonomous Exploration and Exploitation

arXiv:2608.05628v1 Announce Type: new Abstract: Although agent skills equip LLMs with reusable procedural knowledge, manual maintenance suffers from high costs, unscalability, and misalignment. Real-w

SkillMemo: Expert-guided Skill Memory Framework for Compositional Embodied Manipulation

arXiv:2608.05970v1 Announce Type: cross Abstract: Embodied visuomotor models, including Diffusion Policy (DP) and Vision-Language-Action (VLA) models, have demonstrated promising performance on roboti

SkillTFM: Gated Skill Evolution for Training-Free Adaptation of Tabular Foundation Models

model-releasesarxiv-cs-lg

arXiv:2608.06137v1 Announce Type: new Abstract: Tabular data are ubiquitous in real-world applications and are crucial for data-driven prediction and decision-making across science, industry, finance,

Agents

SkillTrace: Multi-Trace Provenance Auditing for LLM-Agent Skill Reuse

arXiv:2608.05204v1 Announce Type: new Abstract: LLM-agent ecosystems are rapidly growing around reusable skills: mixed-modality packages of metadata, natural-language instructions, code, tools, refere

agentsarxiv-cs-ai

SkillTV-Bench: Benchmarking How Well Judges Perform on Skill-Augmented Agentic Execution

arXiv:2608.05573v1 Announce Type: new Abstract: LLM agents increasingly execute long-horizon tasks through tool use and environment interaction, shifting evaluation from final-response scoring to veri

Agents

SkillZip: Contract-Preserving Graph Compression for Scalable Agent Skill Libraries

arXiv:2608.05604v1 Announce Type: cross Abstract: Large Language Models (LLMs) increasingly act as agents whose procedural knowledge is stored in reusable skill packages and loaded at inference time.

agentsarxiv-cs-ai

Sliding Sensors: Configurable Confidence in State Estimation for Continuum Robots

arXiv:2608.05410v1 Announce Type: new Abstract: Continuum robots often operate in uncertain environments, where accurate state estimation is essential for safe interactions. Estimate uncertainty is in

researcharxiv-cs-ro

Small Foundation Models of Human Cognition and Behaviour

arXiv:2608.05224v1 Announce Type: new Abstract: Large language models fine-tuned on human behavioural data have emerged as general-purpose cognitive proxies, but the scale this requires, and whether t

Applications

Sparse Mixture-of-Experts for Non-Uniform Noise Reduction in MRI Images

arXiv:2501.14198v3 Announce Type: replace-cross Abstract: Magnetic Resonance Imaging (MRI) is an essential diagnostic tool in clinical settings, but its utility is often hindered by noise artifacts in

applicationsarxiv-cs-cv

Sparse Mutual Information Graph Averaging for Improving Random Indexing Embeddings

arXiv:2608.05724v1 Announce Type: new Abstract: Sparse word embedding pipelines can avoid dense co-occurrence matrix materialization, dense factorization, and gradient training while still relying on

researcharxiv-cs-cl

Spectral Aliasing Pretext: A novel task for Self-Supervised fault diagnosis in rotating machinery

arXiv:2608.05705v1 Announce Type: cross Abstract: Deep learning is a new way for machinery fault diagnosis but requires extensive labeled data, a scarce resource in industrial settings. We propose Spe

tutorialsarxiv-cs-ai

Spectral Distillation: From Nonlinear Dynamics to Linear State-Space Models

arXiv:2608.05416v1 Announce Type: new Abstract: Can nonlinear dynamical systems be learned through a compact linear state-space representation, without directly solving a non-convex system-identificat

tutorialsarxiv-cs-lg

SR-JEPA: Learning Predictive Latent State in 3D Scenes

arXiv:2608.05774v1 Announce Type: new Abstract: Joint-embedding predictive architectures learn by predicting latent representations of missing observations, yet many masked JEPAs are evaluated primari

tutorialsarxiv-cs-cv

Stability of Ranking-dependent Pair-wise Comparison Patterns in the Analytic Hierarchy Process

arXiv:2608.05958v1 Announce Type: new Abstract: The paper addresses several ranking-dependent decision support methods. Ordinal information on compared objects can be used to improve the quality of ex

STAIL: Semantic Text-Anchored Incremental Learning for Medical Imaging via Large Language Models

arXiv:2608.05808v1 Announce Type: new Abstract: Deep learning models applied to medical image analysis suffer from severe catastrophic forgetting when continually adapting to new clinical tasks in dyn

researcharxiv-cs-cv

STATe-of-Thoughts: Structured Action Templates for Tree-of-Thoughts

arXiv:2602.14265v3 Announce Type: replace Abstract: Inference-Time-Compute (ITC) methods like Best-of-n and Tree-of-Thoughts are meant to produce output candidates that are both high-quality and diver

tutorialsarxiv-cs-cl

StepReflect: Structured UI Transition Reflection for Mobile GUI Agents

arXiv:2608.05587v1 Announce Type: new Abstract: Autonomous mobile GUI agents require accurate action reflection for reliable long-horizon execution. Existing approaches rely on open-ended multimodal r

Stochastic Dynamics on Persistence Diagram Space via Reinforcement Learning

arXiv:2608.06276v1 Announce Type: cross Abstract: Persistence diagrams (PDs) provide stable and interpretable summaries of multiscale topological structure. While substantial progress has been made in

tutorialsarxiv-cs-lg

Stochastic Parrots or Singing in Harmony? Testing Five Leading LLMs for their Ability to Replicate a Human Survey with Synthetic Data

arXiv:2603.00059v3 Announce Type: replace-cross Abstract: How well can AI-derived synthetic research data replicate the responses of human participants? An emerging literature has begun to engage with

Stochasticity Is Not the Hard Part: Reduction and Complexity in Instructional Sequencing over Prerequisite DAGs

arXiv:2608.05455v1 Announce Type: new Abstract: When a student must learn concepts connected by prerequisite dependencies, when does the order of instruction matter, and what does it cost to find the

tutorialsarxiv-cs-ai

StreamArena: Toward Continuous, Interactive, and Long-Horizon Agentic Streaming Video Understanding

model-releasesarxiv-cs-cv

arXiv:2608.05703v1 Announce Type: new Abstract: Deploying autonomous multimodal agents in continuous, real-world environments requires them to ingest unbounded audio-visual streams and maintain hour-s

Studying People to Study AI: Expert Perspectives on the Epistemic Fit and Barriers of Human Research in AI Safety & Ethics

arXiv:2608.05656v1 Announce Type: cross Abstract: Safety risks of AI are becoming increasingly evident in human interactions with AI technologies. The prominent approaches to evaluating these risks fa

StyleComposer: Training-Free Multi-Reference Style Composition

arXiv:2608.05213v1 Announce Type: new Abstract: The style of a painting is not monolithic: color, texture, and structure may come from different sources. Existing reference-guided methods transfer the

researcharxiv-cs-cv

Subliminal Learning is Non-Semantic Distillation

arXiv:2608.05734v1 Announce Type: new Abstract: Subliminal Learning (SL) is a surprising type of generalization displayed by modern language models. It allows the transfer of a bias or behavior from a

Support Operation Factorization: Compositional Readout of Frozen Vision Encoders under Controlled Interventions

arXiv:2608.06174v1 Announce Type: new Abstract: Compositional analysis of frozen vision encoders should determine both what changed and where it changed. Standard factor probes score these axes separa

researcharxiv-cs-cv

Surv-IPTB: An Attention-Based Model for Estimating Individual Probability of Treatment Benefit with Survival Data

arXiv:2608.06288v1 Announce Type: new Abstract: This work presents a novel attention-based framework for estimating the Individual Probability of Treatment Benefit (IPTB) in survival analysis contexts

researcharxiv-cs-lg

Symbol Grounding in Neuro-Symbolic AI: A Gentle Introduction to Reasoning Shortcuts

arXiv:2510.14538v3 Announce Type: replace Abstract: Neuro-symbolic (NeSy) AI aims to develop deep neural networks whose predictions comply with prior knowledge encoding, e.g. safety or structural cons

Task-Conditional Flow Matching for Balanced Multilingual Text Embedding Adaptation

arXiv:2608.05785v1 Announce Type: cross Abstract: Multilingual text embedding models are commonly adapted using a single training objective across diverse tasks, despite different tasks requiring fund

TAU-Bench: From Anomaly Instance Tracking to Fine-Grained Video Anomaly Understanding

model-releasesarxiv-cs-cv

arXiv:2608.05699v1 Announce Type: new Abstract: Humans understand anomalous events through a coherent perceptual process in which they identify the focal instance, follow its behavior as the event unf

Temporal Bridges for Spatial Resolution: Enhancing Climate Data Super-Resolution with Bidirectional Alignment

arXiv:2608.05981v1 Announce Type: new Abstract: High-resolution climate data is crucial for meteorological predictions and for informing decision support across diverse domains. However, the acquisiti

Test-Time Scaling in Reasoning Models Is Not Effective for Knowledge-Intensive Tasks Yet

arXiv:2509.06861v3 Announce Type: replace Abstract: Test-time scaling increases inference-time computation through longer reasoning chains and has shown strong performance gains across many domains. H

Text Generation: A Systematic Literature Review of Tasks, Evaluation, and Challenges

arXiv:2405.15604v4 Announce Type: replace Abstract: Text generation has become more accessible than ever, and the growing interest in these systems, especially those using large language models, has s

safetyarxiv-cs-cl

Text-Guided Refinement of Multi-sequence Glioma Subregion Segmentation with a Vision-Language Foundation Model

model-releasesarxiv-cs-cv

arXiv:2608.05389v1 Announce Type: new Abstract: Background: Accurate glioma subregion delineation is important for radiotherapy planning and longitudinal monitoring, but manual contour correction is t

THBKG: A Temporal Biomedical Knowledge Graph for Decision-Aligned Clinical Advancement Prediction

model-releasesarxiv-cs-lg

arXiv:2608.05982v1 Announce Type: new Abstract: Inadequate target--disease linkage accounts for 40--50% of Phase~II efficacy failures, so anticipating which programmes will advance would let sponsors

The Bitter Lesson of Tool Calling

model-releasesarxiv-cs-cl

arXiv:2608.06370v1 Announce Type: new Abstract: Tool use transforms LLMs into agents that act beyond their training data, and for code-capable models, programmatic tool calling extends this further by

The Closing Window: How Governments Could Lose Their Ability to Restrain Advanced AI

arXiv:2608.05173v1 Announce Type: cross Abstract: As AI capabilities advance, AI systems will pose greater risks to national security and potentially humanity as a whole. Governments may eventually co

The em-dash em-beds in Congress: A population-level rise in em-dash frequency in U.S. congressional press releases at the dawn of the large-language-model era, 2021-2025

arXiv:2608.05889v1 Announce Type: cross Abstract: Large language models (LLMs) can leave small stylistic traces in text written with their help. The most discussed is the em-dash (U+2014), especially

The ethics of artificial intelligence in the life sciences: Universality, cultural diversity and an architecture of care

arXiv:2608.05436v1 Announce Type: cross Abstract: The life sciences and health research have started to benefit from artificial intelligence, which raises ethical concerns that are real but, we argue,

The Ignition Index: Measuring Global Workspace Dynamics in Language Models

arXiv:2608.05160v1 Announce Type: new Abstract: We introduce the Ignition Index (I), a validated scalar metric that operationalizes Global Workspace Theory's (GWT) all-or-none ignition prediction in t

The Illusion of Visual Tool-Use: A Causal Audit of Thinking with Images

arXiv:2608.06270v1 Announce Type: new Abstract: The 'thinking-with-images' paradigm equips multimodal LLMs with active visual operations such as crop-and-zoom. However, models using these operations o

The interface of intonation and lexical tone: Boundary phenomena in Mandarin varieties

arXiv:2608.05364v1 Announce Type: new Abstract: This chapter explores the intricate interplay between intonation and tone in Mandarin Chinese varieties, focusing on f0, the primary acoustic cue for bo

researcharxiv-cs-cl