Towards Data Science
Jun 22
How to Use Claude Code in Your Browser
Learn how to apply coding agents to verify work in your browser. The post How to Use Claude Code in Your Browser appeared first on Towards Data Science .
Large language models
Model releases, architecture work and prompting research on large language models — from frontier-lab announcements to the arXiv papers behind them.
Hugging Face Trending Papers
Jun 22
Automated Semantic Fault Localization in SysML v2: A Human-in-the-Loop Framework Using Knowledge-Graph Augmented LLMs
SysML v2's textual syntax enables compiler-based validation of model structure and language conformance. However, semantic mistakes that preserve syntactic validity but violate domain rules cannot be detected through compilers.
Hugging Face Trending Papers
Jun 22
Unlocking In-Context Learning in Audio-Language Models from Decentralized Medical Audio
Clinical audio diagnosis in low-resource settings requires models that identify conditions from minimal examples without large annotated corpora. We propose Federated Self-Contextualization (FSC), a multimodal language model framework for in-context clinical audio diagnosis across federated hospital clients.
Hugging Face Trending Papers
Jun 22
MambaADv2: Evolving Duality-enhanced State Space Model for Unsupervised Anomaly Detection
While recent advancements in anomaly detection have demonstrated the efficacy of CNN- and Transformer-based approaches, these architectures face inherent limitations: CNNs struggle to capture long-range dependencies, whereas Transformers suffer from quadratic computational complexity. Consequently, Mamba-based architectures have attracted considerable attention, as they successfully combine superior long-range dependency modeling with linear computational complexity.
Hugging Face Trending Papers
Jun 22
LUMINA-26: Low-Light Understanding for Modeling and Interpreting Night-time Actions
Low-light human action recognition remains a challenging problem due to poor illumination, amplified noise, motion ambiguity, and diverse real-world scenes. Existing low-light datasets often lack sufficient action diversity, capture realism, or balanced class distribution, limiting the development of robust models.
OpenAI Blog
Jun 22
Daybreak: Tools for securing every organization in the world
OpenAI introduces new Daybreak tools, including Codex Security and GPT-5. 5-Cyber, to help organizations find, validate, and patch vulnerabilities at scale.
Hugging Face Trending Papers
Jun 22
PIVOTSBench: Evaluating Fine-Grained Interpersonal Relationship Reasoning in Multimodal Large Language Models
Humans possess an innate ability to understand fine-grained interpersonal relationships, which is central to everyday social interactions. Although such reasoning is inherently multimodal, it remains largely unexplored by existing multimodal large language models (MLLMs).
Hugging Face Trending Papers
Jun 22
IPO Finance Agent: Evaluation of LLM Financial Analysts beyond Finance Agent v2, with Automated Rubric Generation -- the Case of the SpaceX (SPCX) IPO
Finance Agent v2 (by Vals AI) has emerged as the reference benchmark for evaluating both Anthropic Claude and OpenAI ChatGPT frontier language models on financial tasks. However, it narrowly deals with periodic reporting from publicly traded companies (SEC 10-K and 10-Q filings), and its agentic harness relies on naive, unenriched chunk retrieval.
Hugging Face Trending Papers
Jun 22
Have You Ever Seen Them? Entity-level Membership Inference through Interrogating Large Language Models
Large Language Models (LLMs) raise growing concerns about privacy leakage and copyright compliance. Membership inference is a key tool for assessing such risks, but existing studies mainly focus on whether specific samples or sample-based data units are used for training.
Hugging Face Trending Papers
Jun 22
Understanding Knowledge Distillation in Post-Training: When It Helps and When It Fails
Large language models (LLMs) achieve strong performance across many tasks, but their high computational cost limits deployment in resource-constrained environments. Knowledge Distillation (KD) offers a practical solution by transferring knowledge from a teacher model of a larger size to a smaller student model.
Hugging Face Trending Papers
Jun 22
Provable Benefits of RLVR over SFT for Reasoning Models: Learning to Backtrack Efficiently
Recent advances in large language models (LLMs) have demonstrated that reinforcement fine-tuning of pretrained base models can lead to significant gains in reasoning performance at inference time. In this work, we theoretically analyze why reinforcement fine-tuning induces better reasoning ability than purely supervised fine-tuning (SFT) methods.
Hugging Face Trending Papers
Jun 22
Graph-Enhanced Large Language Models for Spatial Search
There have been many recent improvements in the ability of Large Language Models (LLMs) to perform complex tasks and answer domain-specific questions through techniques like Retrieval Augmented Generation (RAG). However, reasoning abilities of LLMs, including spatial reasoning abilities, are still lacking.
Hugging Face Trending Papers
Jun 22
Physiology-Aware CNN and Zero-Shot Multimodal LLMs for ECG Image Classification: A Comparative Study
Multimodal large language models (LLMs) are increasingly adopted to interpret 12-lead ECG images, though the interpretations often lack validation. However, ECG image understanding significantly differs from general images as it depends on precise waveform morphology, lead relationships and accurate interval measurements.
Hugging Face Trending Papers
Jun 22
SingGuard: A Policy-Adaptive Multimodal LLM Guardrail with Dynamic Reasoning
Vision-language models (VLMs) are increasingly deployed in consumer, medical, financial, and enterprise applications. This broad deployment expands the safety surface: risks can arise from multimodal question answering, assistant responses, and cross-modal composition, while moderation policies may vary across products, regions, and deployment stages.
Hugging Face Trending Papers
Jun 22
VideoLatent: Video-Language Learning via Latent Self-Forcing
Recent advancements in chain-of-thought (CoT) reasoning have shown promise in enhancing video understanding and reasoning capabilities of multimodal large language models (MLLMs). However, existing CoT-based MLLMs require labor-intensive CoT annotations and incur substantial training and inference overhead.
Hugging Face Trending Papers
Jun 22
RaMem: Contextual Reinstatement for Long-term Agentic Memory
Long-term memory has become increasingly important for LLM agents that operate across extended interactions and evolving task contexts. Recent memory systems have made past experiences more persistent, compact, and retrievable, but retrieval alone does not ensure that a memory provides valid evidence for the current query.
Hugging Face Trending Papers
Jun 22
The Origins of Stochasticity: Comprehensive Investigations on Uncertainty Quantification for Large Language Models
Recent advancements in Large Language Models (LLMs) have enabled sophisticated reasoning and content generation, yet their inherent stochasticity poses significant challenges for ensuring predictive credibility. While traditional uncertainty taxonomy paradigms, such as the dichotomy of aleatoric and epistemic uncertainties, provide conceptual foundations, they often fail to capture the multi-component and multi-stage nature of LLM generation and struggle to evaluate the effectiveness of various Uncertainty Quantification (UQ) methods.
Hugging Face Trending Papers
Jun 22
Learning Moral Diversity: Modelling Individual Perspectives in Moral Classification of Texts
Understanding moral values in social media text offers insight into moral judgement formation, and supervised NLP models trained on crowdsourced data have achieved strong classification performance. However, most approaches simplify the problem by aggregating multiple annotators' labels into a single "ground truth", overlooking the inherent subjectivity of the task.
Hugging Face Trending Papers
Jun 22
GroundEval: A Deterministic Replacement for LLM-as-Judge in Stateful Agent Evaluation
Before letting an agent operate over real context, can you prove it used the right evidence? GroundEval turns that question into a deterministic test of what the agent searched, fetched, cited, and was permitted to access.
OpenAI Blog
Jun 21
Samsung Electronics brings ChatGPT and Codex to employees
Samsung Electronics deploys ChatGPT Enterprise and Codex to employees worldwide, marking one of OpenAI’s largest enterprise AI rollouts.