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Newest papers, page 231
IterSynth: Rethinking Deep Search Agents via Role-Decoupled Iterative Synthesis
Deep search requires LLM agents to decompose complex queries, search for evidence, and synthesize grounded answers, yet existing ReAct-style agents suffer from two limitations: role coupling, where…Two Emojis of Difference: What Multilingual Affective Generation Benchmarks Actually Measure
We audit a multilingual affective generation benchmark eight instruction-tuned LLMs producing emoji summaries for 17,100 Bangla, English and Hindi sentences, with 6,960 human judgements and find its…YODAS v3: Over 1 Million Hours of High-Bandwidth, Stereophonic, Multilingual Speech
We present YODAS v3, a weakly-labeled speech corpus containing over 1.1 million hours of 48kHz multi-channel audio in 147 languages, released under a CC BY 3.0 license.CodeGraph: Open-Taxonomy Knowledge Graph for Source Code with Wikidata Grounding
Public software repositories, like GitHub and Software Heritage Archive, store billions of files, yet extracting their implicit engineering knowledge ---i.e., the algorithms they implement, the…TTLab at AlexandriaX-2026: A Fine-Tuned Surface Tagger for Arabic Machine-Translation Error-Span Detection and Classification
We present TTLab's submission to the AlexandriaX-2026 Subtask~3 on Arabic MT error span detection and classification.TTLab at StanceEval-2026: A Cloze-Style Prompting Approach for Arabic-Language Stance Detection (CLASP-Ar)
Arabic-language stance detection remains challenging, and previous shared-task systems have largely relied on multitask learning and ensembles.C3M: Cross-Session Multimodal Memory Maintenance for Long-Horizon Tasks
Long-horizon tasks require preserving and later recovering cross-session evidence under a bounded, query-blind memory budget.JEV vs. LLMs as Rubric Judges: Cheaper, Faster, and Wrong in the Same Places
We ask whether Jev, a typed classifier that returns probabilities over permitted answers without generating text, can replace an LLM rubric judge.TimeBraid: Unifying Time Series and Language for Understanding and Forecasting
We present TimeBraid, a series of unified time-series and language models that align pretrained language models and pretrained time-series foundation models through interleaved global residual…Benchmarking and Domain Adaptation of Automatic Speech Recognition (ASR) for Adolescent Health Communication in Ghanaian Languages
This paper presents an end-to-end study of automatic speech recognition (ASR) for adolescent health communication in three Ghanaian languages (Twi, Dagbani, and Ewe).Adaptive Fisher-Whitened Cross-Covariance for Low-Resource Speech Recognition
Adapting multilingual speech foundation models to low-resource languages remains difficult, especially for languages that are poorly represented during pre-training.Learning to Ideate for Scientific Impact
Scientific ideation is increasingly mediated by large language models, but current ideation systems are usually trained and evaluated on immediately judgeable proxies such as novelty, clarity, and…CORDIAL: Calibrating Ordinal LLM Outputs from Few Labels
A large language model (LLM) can turn a text into a distribution over an ordered scale, but that distribution is a noisy measurement: saturated, compressed or exaggerated, and biased in a consistent…ChunkRank: Model-Aware Text Chunking and Abstention-Aware Answer Selection for LLM Pipelines
We present ChunkRank, an open-source Python library that derives chunk boundaries from a target model's tokenizer and context window, and selects an answer among candidates produced independently…PUBG Ally: A Conversational Embodied Agent as an AI Teammate
We introduce PUBG Ally, an embodied agent for PUBG: BATTLEGROUNDS that can reason, act autonomously, and play alongside players as a voice-enabled teammate.Your Transformer Can Hold Two Thoughts at Once: Evidence of Linear Superposition in LLMs
While Large Language Models (LLMs) rely on highly non-linear components, in this work we demonstrate that they exhibit fundamental linearity: when inputs from distinct text streams are linearly…Encoded but Not Decoded: Layer-Localized Evidence for a Three-Level Gap in LLM Syntax
A language model can fail a syntactic test in two distinct ways: by not encoding the relevant structure, or by encoding it but failing to use it at the output.Multi-Task Learning by using Contextualized Word Representations for Syntactic Parsing of a Morphologically Rich Language
We address the challenge of syntactic parsing for Urdu, a morphologically rich language, and present state-of-the-art results for both constituency and dependency parsing.MILO: Efficient Many-shot In-Context Learning with Block-wise Low-rank Compression
Many-shot in-context learning (ICL) enables large language models (LLMs) to adapt to complex tasks by conditioning on thousands of demonstration examples, but this paradigm shifts the inference…Cultural Divergence Preservation: Diagnosing Flattening and Caricature in LLM-Simulated Survey Populations
Large language models (LLMs) are increasingly used as synthetic survey respondents to estimate population response distributions.