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Newest papers, page 47
OmniBrain-0: A Unified Agentic Model for Embodied Intelligence
General-purpose embodied intelligence requires robots to coordinate diverse skills over long horizons, track task progress, and recover from failures.How Much Does the Hint Matter? Scope Conditions for Hindsight Self-Distillation in Financial Reasoning
Financial institutions operating under data-residency constraints are restricted to open-weight models small enough to locally host, which trail frontier systems on multi-step quantitative reasoning.FinLLM-KG: Knowledge Graph-Enhanced LLMs for Financial Sentiment Analysis in Algorithmic Trading
Recent advances in Generative AI have substantially improved financial sentiment analysis through post-trained financial large language models (LLMs).Beyond Update Counts: A Control Map for Evaluating Test-Time Model Updates
Test-time updating lets a language model change persistent state after training---such as model weights, adapter parameters, or a memory module---before or while answering queries.ConformalMOS: Uncertainty-Aware MOS Prediction with Conformal Intervals and Ordinal Modeling
Accurate prediction of human Mean Opinion Scores (MOS) is crucial for evaluating synthetic speech quality in text-to-speech (TTS) and voice conversion (VC).Don't Pick a Winner: Knowledge Conflicts Need a Prior, Not a Rule
A retrieval-augmented language model answers from two sources, the retrieved context and its own knowledge, and the two disagree whenever the context is incomplete or wrong.3, 7, 14, 17, 42: Instruction Tuning Installs and Sharpens Number-Choice Heuristics in Language Models
We measure, without sampling error, the probability a language model assigns to each integer from 1 to N when asked for a random number.Lipi-Ghor: A Large-Scale, Diarized, Multi-Domain Bengali Speech Corpus and a Scalable Pipeline for Building It
Bengali, spoken by over 230 million people, remains severely under-resourced in spoken language research.Frankly Speaking: The Company Election Integrity Keeps in Congressional Communication
Election integrity is a shared commitment in American politics, but Democrats and Republicans in Congress increasingly mean different things by it.LLM Hallucination Detection via Low-rank Multilinear Decomposition
Large language models (LLMs) frequently generate fluent yet factually incorrect responses, raising concerns about their reliability.Learning to Read Braille: Benchmarking and Improving Braille Recognition Capabilities of VLMs
Despite rapid progress in visual understanding and document transcription, modern vision-language models (VLMs) struggle with a fundamental accessibility task: reading Braille from images.Base Models Can Detect Hidden Intentions that Prompted Classifiers Miss
The Persona Selection Model (PSM) posits that post-training selects a persona the model learned during pre-training.Beyond IceBERT: Open-Data ModernBERT Encoders for Icelandic from 12M to 1B Parameters
IceBERT, the reference encoder for Icelandic, found that a cleaned web crawl is enough to train a strong model and that starting from a multilingual model can help on some tasks.Cross-modal Steering Vectors Exist Across Both Image and Text Generation
Are concepts and mechanisms unified across modalities in current AI models, or instead implemented separately for each one?Detect Before You Disambiguate: Perturbation-Based Input Ambiguity Detection in LLMs
Large language models (LLMs) often answer ambiguous inputs as if they had a single intended meaning.AK_QMUL at ArGuard Shared Tasks: A Single Fine-Tuned JAIS for Arabic Harmful-Prompt Detection
We present AK_QMUL's submissions to the ArGuard-2026 shared tasks on Arabic harmful-prompt detection: a binary safe/unsafe task (B1) and a seven-way harm-domain task (B2).SOMA: A Benchmark for Fine-Grained Egocentric Behavior and Body-Motion Understanding
Perceiving human body motion is critical for multimodal systems that understand and assist people.Relevance-Guided Residual Calibration for Spectral Compression of Dense Retrieval Embeddings
Spectral compression reduces the storage and scoring costs of dense retrieval by projecting embeddings onto a smaller principal subspace.Continual Learning Exam: Benchmarking Long-Horizon RSI and Experiential Learning in LLM Agents
Continual learning is the ability of LLM agents to improve over time by acquiring, refining, and applying knowledge from experience while retaining useful prior knowledge.How Do Small Coding Agents Use Code Graphs and Embeddings?
Coding agents are given embedding search and code-graph tools on the premise that a repository's structure is something the model lacks and the tool supplies.