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Newest papers, page 126
A Scaled-Up Empirical Study of Syntactic Language Models
Syntactic language models (SLMs) that generate sentences along with their syntactic tree structures have shown promise in both syntactic generalization and downstream tasks.Label Collapse in Diffusion Language Model In-Context Learning
In-context learning (ICL) applies large language models to new tasks by prepending a few labeled demonstrations to a query.ANCHOR: Assessing Naturalistic Constraint Hierarchies and Ordering in Repository-Grounded Agentic Coding
For repository-grounded coding agents, a functionally correct patch is not necessarily an acceptable one: developers also constrain how the task must be carried out-modification scope, workflow…Davinci-Tool: Scaling Agentic Tool-Use Supervision with Verifiable Executable Environments
Reliable agentic tool use requires training data that pair diverse multi-step workflows with executable evidence that the requested outcomes were achieved.SpecGuardBench: Can Coding Agents Construct Reliable Validation Harnesses from Natural Language Specifications?
As coding agents become more capable, tests remain the primary evidence for judging whether their code is correct.Estimating Uncertainty of Omnimodal Large Language Models via External Omnimodal Embeddings
Recent work has investigated Omni-modal Large Language Models (OLLMs), models which can take multiple modalities and their combinations as input, as a way forward to have systems really capable of…Lexical Redefinition Reveals Context-Sensitive Instruction Following
How do language models reconcile conflicting contextual evidence within a prompt?SarcasTraps: Effect of Sarcasm on Turkish Hate Speech Detection
Standard hate speech detection datasets often emphasize explicit harmful language, but directed harm can also be expressed indirectly, without clearly hateful wording.Event Memory and Narrative Dynamics: A Large Language Model Framework for Multidimensional State Spaces
Studying event memory requires defining events and their relationships within remembered experience.Predicting Mental Health Help-Seeking Behaviour on Reddit: A Survival Analysis of Linguistic and Behavioural Signals
Most prior work on predicting mental health help-seeking treats it as post-hoc classification of users already active in clinical communities, which cannot tell whether someone approaching a…Understanding Personalization Gains in Whisper
Whisper-style ASR models provide strong zero-shot transcription, but their residual errors are not evenly distributed across datasets, recording conditions, and metadata-based groups.MENTOR: Procedural Shielding of Tool-Using LLM Agents
Tool-using LLM agents are increasingly used to automate workflows governed by procedural manuals, such as company rules for booking travel or procuring hardware.Beyond Model Bias: Cross-Entropy Based Rankings in Literary and Academic Texts Remain Stable across Small Language Models
While language models provide powerful mechanisms for evaluating textual predictability, it remains unclear whether the relative extents of LM surprisal remain stable across models.AD4EDU: Benchmarking University Lecture Audio Description across Accessibility Standards, Metrics, and Learner Preferences
Audio description (AD) aims to enhance the accessibility of visual media for blind and low-vision (BLV) persons.UZHCL_for_the_win at Touche: Encoder Fine-Tuning, Synthetic Augmentation, and an Underpowered Encoder-LLM Comparison
Online discussions on platforms like Reddit are a productive testbed for fallacy detection: short texts, broad topical range, and the full inventory of informal fallacies.Towards Universal Calibration for In-Context Classification
In-Context Learning (ICL) has received a lot of interest recently due to its ability to improve classification accuracy for new tasks without having to fine-tune the model over these tasks.Calibrated Typed Decisions for Entity, Relation, and Event Extraction
Information extraction models often perform well on the datasets they are trained on, but transferring to new domains and annotation guidelines remains challenging.Gluing Local Contexts into Global Meaning: A Sheaf-Theoretic Decomposition of Transformer Representations
Existing interpretability tools do not test whether a representation keeps the same content when only the phrasing changes.When LLM Agents See a Conflict but Still Proceed: Cross-Domain Dependencies in Network Slicing
Future AI-native networks are being designed to apply autonomous agents built on large language models (LLMs) in network management through intents.D2: High-Capability Full-Duplex Spoken Language Models from Half-Duplex Backbones
Full-duplex spoken language models (FD-SLMs) support simultaneous listening and speaking, but often lag behind half-duplex spoken language models (HD-SLMs) in general capabilities.