TechniqueRLHF / Alignment8 recent entries12 Aug 2026Fisher8: Stabilizing Neural Heteroscedastic Regression via Output-Layer Fisher GeometryarXiv:2608.10374v1 Announce Type: new Abstract: Training neural networks to jointly predict mean and uncertainty estimates from noisy observations can be unstable, prompting a series of independent st→12 Aug 2026EweAcT: Ewe behaviour aligned to accelerometer data for activity monitoring in extensive grazing systemsarXiv:2608.09943v1 Announce Type: cross Abstract: Monitoring livestock behaviour under extensive conditions would provide valuable insights to assess animal adaption to environmental perturbations in
TechniqueRAG8 recent entries11 Aug 2026Guardian Crawler: Retrieval-First Knowledge Discovery with Bounded LLM Augmentation for Noisy Web IntelligencearXiv:2608.08994v1 Announce Type: cross Abstract: Retrieving relevant evidence from noisy web data is challenging, particularly in sensitive domains containing incomplete reports, heterogeneous langua→11 Aug 2026DS@GT ARC at Touche: Large Language Models for Retrieval-Augmented DebatearXiv:2608.08143v1 Announce Type: cross Abstract: We extend the DS@GT ARC working-note submission to the Touche 2025 Retrieval-Augmented Debate task. The task has two subtasks: generating the next utt→11 Aug 2026AnchorFold: A Focus-Then-Fold Framework via Recursive Attention Propagation for Efficient Multi-Vector Visual Document RetrievalarXiv:2608.08732v1 Announce Type: cross Abstract: Multi-vector vision-language retrievers enable fine-grained Visual Document Retrieval (VDR) through late interaction, but storing and scoring hundreds→11 Aug 2026AkasicDB: Demonstrating Omni RAG with a Unified Vector-Graph-Relational DBMSarXiv:2608.09214v1 Announce Type: cross Abstract: Recent Retrieval-Augmented Generation (RAG) systems increasingly combine vector retrieval with structured knowledge, such as Graph RAG and Filtered ve→12 Aug 2026Post-Calibration Reliability Reranking of Relevance Decisions via Label-wise Monotone ProjectionarXiv:2608.10406v1 Announce Type: cross Abstract: Web search, product search, and question-answering retrieval systems often assign a relevance label and confidence score to each query-candidate pair.→12 Aug 2026Order Matters: LVLMs as Judges for Temporal Reasoning in Image SequencesarXiv:2608.10908v1 Announce Type: cross Abstract: As generative multimedia evolves from static image synthesis to complex, interleaved visual narratives, a foundational bottleneck has emerged: the jud→12 Aug 2026Multi-Granular Rationale-Guided Molecular LLM for Property PredictionarXiv:2608.10480v1 Announce Type: new Abstract: Large language models (LLMs) are widely applied across chemical tasks, such as molecular property prediction, which underpins drug discovery. Molecular →12 Aug 2026GraFine: Retrieval-Time Refinement for Efficient Graph RAG over Corpus GraphsarXiv:2601.18579v2 Announce Type: replace-cross Abstract: Graph RAG on corpus graphs enhances retrieval by leveraging intermediate node content as contextual clues to uncover unretrieved oracle nodes.
TechniqueAgents8 recent entries11 Aug 2026A foundation model of numerical intelligence with cross-disciplinary generalizationarXiv:2607.28432v2 Announce Type: replace Abstract: Intelligence is commonly understood as the ability to acquire and apply knowledge, adapt to unfamiliar situations and solve new problems. Large lang→12 Aug 2026StreamFlow: Dynamic Memory Flows for Streaming Video UnderstandingarXiv:2608.10949v1 Announce Type: cross Abstract: Streaming video understanding requires multimodal large language models (MLLMs) to preserve relevant evidence from continuously evolving streams under→12 Aug 2026SkillZip: Evaluation-Free Skill Compression for Self-Evolving Agents by Discovering Reusable StructurearXiv:2608.11079v1 Announce Type: new Abstract: Self-evolving agents accumulate reusable skills by appending successful procedures and failure fixes. Over time, the same requirement is often restated →12 Aug 2026Self-Correcting Long-Horizon Search Agents via Tree-Structured MemoryarXiv:2608.10676v1 Announce Type: new Abstract: Large language model (LLM)-based search agents answer questions through multi-step interactions with external environments. However, providing complete →12 Aug 2026Post-Hoc Sparse Coding of Latent Communication Between Vision-Language Model AgentsarXiv:2608.10198v1 Announce Type: new Abstract: Latent-space communication allows heterogeneous vision-language model agents to exchange continuous representations without serializing visual and reaso→12 Aug 2026Order Matters: LVLMs as Judges for Temporal Reasoning in Image SequencesarXiv:2608.10908v1 Announce Type: cross Abstract: As generative multimedia evolves from static image synthesis to complex, interleaved visual narratives, a foundational bottleneck has emerged: the jud→12 Aug 2026Evaluating Rational Contracting in Natural LanguagearXiv:2608.10475v1 Announce Type: new Abstract: The emergence of language-based AI agents promises to transform the scope of machine economic activity. Instead of just proposing bids or following hard→12 Aug 2026Do LLMs Benefit From Their Own Words?arXiv:2602.24287v2 Announce Type: replace-cross Abstract: In multi-turn conversations, large language models typically condition on the full conversation history: both past user prompts and assistant
TechniqueFine-tuning8 recent entries12 Aug 2026Protecting Creative Writing Copyright against AI Imitation via Implicit WatermarkingarXiv:2504.00035v4 Announce Type: replace-cross Abstract: Large language models (LLMs) enable powerful knowledge injection through approaches such as in-context learning and fine-tuning, but they also→12 Aug 2026Multi-Granular Rationale-Guided Molecular LLM for Property PredictionarXiv:2608.10480v1 Announce Type: new Abstract: Large language models (LLMs) are widely applied across chemical tasks, such as molecular property prediction, which underpins drug discovery. Molecular →12 Aug 2026MoE Proxy Models for Low-Cost Failure Reproduction and Diagnosis in LLM RL Post-TrainingarXiv:2608.10823v1 Announce Type: new Abstract: Reinforcement learning (RL) post-training of large language models (LLMs) is computationally intensive and involves complex system pipelines with substa→12 Aug 2026GridVAD: Open-Set Video Anomaly Detection via Spatial Reasoning over Stratified Frame GridsarXiv:2603.25467v3 Announce Type: replace Abstract: Vision-Language Models (VLMs) are powerful open-set reasoners, yet their direct use as anomaly detectors in video surveillance is fragile: without c→12 Aug 2026DEFT: Data-Efficient Frequency-domain Top-k Sampling via Inverse Discrete Fourier Transform for Spatiotemporal Dynamical Systems ModelingarXiv:2608.11019v1 Announce Type: new Abstract: Modeling spatiotemporal dynamical systems governed by partial differential equations (PDEs) poses two major challenges: it either requires expensive phy→12 Aug 2026Decodable But Not Detachable: Training Data Granularity Determines Parametric Modularity in Large Language ModelsarXiv:2608.10214v1 Announce Type: new Abstract: Do large language models contain domain-specific parametric shells: concentrated, causally necessary neuron populations whose removal selectively degrad→12 Aug 2026Can Computational Reducibility Lead to Transferable Models for Graph Combinatorial Optimization?arXiv:2603.02462v2 Announce Type: replace-cross Abstract: A key challenge in developing unified neural solvers for combinatorial optimization (CO) is the efficient generalization of models from a give→12 Aug 2026A Fixed-Point Neural Operator for Size- and Functional-Transferable Hamiltonian PredictionarXiv:2606.14498v2 Announce Type: replace-cross Abstract: Predicting the Kohn-Sham Hamiltonian with machine learning can accelerate density functional theory while retaining access to molecular orbita
TechniqueMultimodal8 recent entries12 Aug 2026Foundation Model-Enabled Efficient Data Sampling (FEEDS): A label-efficient training strategy for pan-cancer, multi-tracer PET/CT datasetsarXiv:2608.11076v1 Announce Type: new Abstract: Automated lesion segmentation in whole-body PET/CT imaging can assist clinicians with cancer detection, staging, and treatment planning across radiotrac→12 Aug 2026Evaluating Semantic and Spatial Guidance for Foundation Model Segmentation of Small-Scale PV in Remote Sensing ImageryarXiv:2608.10801v1 Announce Type: new Abstract: Spatio-temporal PV data are essential for understanding adoption processes in off-grid regions, yet such data remain largely unavailable. Automated segm→12 Aug 2026Eleven Years of BRACIS: A Meta-Scientific Study of the Brazilian Conference on Intelligent SystemsarXiv:2608.09964v1 Announce Type: cross Abstract: The Brazilian Conference on Intelligent Systems (BRACIS) is the main national venue for Artificial Intelligence research in Brazil, hosted by the Braz→12 Aug 2026Dynamic Context Adapters: Efficiently Infusing History into Vision-and-Language ModelsarXiv:2608.10525v1 Announce Type: cross Abstract: Historical context integration presents a fundamental challenge for Vision-Language Models (VLMs) in sequential decision-making tasks. Current VLMs pr→12 Aug 2026DocLang: a markup language for LLMsIBM has introduced **DocLang**, a new markup language specifically designed for large‑language models (LLMs). Developed by lead researcher Peter Staar and IBM’s document‑parsing team, DocLang aims to →12 Aug 2026Conversational versus Dashboard Explainable AI for UAV Intrusion Detection: An Empirical Study of Operator Trust and ReliancearXiv:2608.10434v1 Announce Type: new Abstract: Machine learning-based Intrusion Detection Systems (IDS) have demonstrated superior performance in securing Unmanned Aerial Vehicle (UAV) networks. Howe→12 Aug 2026CausalSplat: Towards Comprehensive Hierarchical Reasoning in 3D Gaussian SplattingarXiv:2608.11150v1 Announce Type: new Abstract: While 3D Gaussian Splatting (3DGS) has advanced open vocabulary scene understanding, existing methods remain confined to explicit queries. They struggle→12 Aug 2026Capturing Uncertainty in Human Motion for Representation Learning in SoccerarXiv:2608.11203v1 Announce Type: new Abstract: This paper presents a self-supervised representation learning framework for understanding 3D skeleton-based human motion in soccer, using future motion
TechniqueSafety8 recent entries12 May 2026Learning When to Trust LLM Priors: A Validated Framework for Semantic Prior IntegrationarXiv:2601.21410v3 Announce Type: replace-cross Abstract: Large language models (LLMs) encode rich semantic knowledge that can be useful for supervised learning, but their outputs are unreliable as st→12 May 2026Intrinsic Guardrails: How Semantic Geometry of Personality Interacts with Emergent Misalignment in LLMsarXiv:2605.10633v1 Announce Type: cross Abstract: Fine-tuning Large Language Models (LLMs) on benign narrow data can sometimes induce broad harmful behaviors, a vulnerability termed emergent misalignm→25 May 2026Call for Papers - Workshop on Unlearning and Model Editing U&ME at ECCV 2026 [R]This call for papers announces a workshop focused on the growing need for efficient and effective techniques for editing trained models, especially large generative models. The workshop solicits paper→4 Jun 2026SANE Schema-aware Natural-language Evaluation of Biological DataarXiv:2606.04500v1 Announce Type: new Abstract: High-throughput microscopy generates large, structured datasets capturing cellular responses to pharmacological perturbations, but accessing these datas→9 Jun 2026What the Eyes See, the LLMs Miss: Exploiting Human Perception for Adversarial Text AttacksarXiv:2606.09700v1 Announce Type: cross Abstract: Large language model (LLM)-powered content moderation systems have become a critical defense against harmful online content. However, these systems pr→24 Jun 2026The best way to understand a complex system is via edge cases and failure modes, because they define the contour of the system.Edge cases and failure modes reveal the fundamental boundaries and constraints of complex systems more effectively than typical operations, making them valuable for understanding system behavior and l→30 Jun 2026Defending Against Harmful Supervision Hidden in Benign SamplesarXiv:2606.30263v1 Announce Type: cross Abstract: Existing defenses are effective when harmful content is explicitly mixed into downstream fine-tuning data, but crafted samples can instead hide harmfu→4 Aug 2026Training-Free Out-of-Distribution Detection for Pathology Whole-Slide ImagesarXiv:2608.01407v1 Announce Type: new Abstract: Safe deployment of AI methods in medicine requires robust guardrails that detect when input data deviate from the training distribution to ensure that m