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Newest papers, page 77
TempoMoE: Identifying and Steering Fast-Slow Thinking Experts for Efficient Multimodal Reasoning
Multimodal Mixture-of-Experts (MoE) reasoning models rely on long chain-of-thought (CoT) for complex tasks, yet often overthink easy inputs, increasing token cost and latency, and sometimes…Scaling Synthetic Pre-training Data and Evaluation for Indic LLMs
Building capable language models for India requires scalable multilingual data and robust evaluation.Accelerated Drift of Scientific Prose in the LLM Era: Evidence from an Interrupted Time-Series Analysis
Every scientific text is embedded in the writing norms of its time: it reflects earlier publications while also shaping the texts that follow.Understanding When Reflective Prompt and Skill Optimization Helps on Locally Served Reasoning Models: A Two-Model Study of GEPA and SkillOpt
Reflective text-space optimizers such as GEPA and SkillOpt have reported large gains on frontier and mid-size models.Decision4Rec: A Jev-Inspired Framework of Decision Models on Knowledge and Active Graphs for Multi-Agent Recommender Systems
Decision models, such as the commercial Jev, are language models that return one probability for each option of a question instead of generating text.Balance-Aware Pivot Selection for Parallel Diffusion LLM Decoding
Diffusion language models enable parallel token generation, offering a promising alternative to sequential autoregressive decoding.Honeyed Words, Hidden Daggers: Benchmarking and Training LLMs to See Through Mock Politeness
The Chinese idiom "kou mi fu jian" ("honeyed words, hidden daggers") names speech that is polite in form but hostile in function.DeepSEA: A Multilingual Evaluation Benchmark for Southeast Asia
While language models have demonstrated remarkable capabilities, their performance remains disproportionately skewed towards high-resource languages.VISAGENT: An Agent-Based End-to-End Voice Interaction System
Voice-based public services have evolved from manual switchboards to intelligent platforms to meet modern user needs.Conditional information Retrieval for Longitudinal Survey Harmonisation
Identifying conceptually equivalent questions across different surveys is a challenging information retrieval task where surface-level textual similarity is insufficient.Reading Time Modeling with Pixel-Based Language Models
Tokenization-free, pixel-based language models (PLMs) have recently been proposed as an alternative to conventional token-based language models (TLMs), typically motivated by practical…VEILED-SH: Vulnerability Expression through Indirect Language Evaluation Dataset (Self-Harm)
AI systems may miss indirect, culturally situated distress or provide support mismatched to the application context.Rethinking BPE: Merge Selection as Model Selection
Subword tokenization methods such as Byte-Pair Encoding (BPE) are a core component of modern language models; yet, tokenizer capacity remains typically determined by a fixed merge budget, chosen…Heartbeat Thinking: Speculative Reasoning and Tool Execution While Listening in Realtime Voice Agents
Tool-using voice agents often leave users waiting after speech ends, even when actionable information arrives earlier in the request.Shaping the Document, Not the Model: Optimized Suffixes for Context Following
When a user supplies a document and wants the answer drawn from it, a language model is expected to follow it even when it contradicts its parametric knowledge.Machina Pauliana: A neuro-symbolic approach to the actio pauliana in Dutch insolvency law
Applying a legal provision frequently requires both structured rule-based reasoning and sensitivity to open-textured terms developed in case law.AudioScorer: Learning Question-Aware Token Relevance for Large Audio Language Models
Large Audio Language Models (LALMs) reason over speech, environmental sounds, music, and other acoustic information.Answering While You Type: Optimizing Time-to-Answer with Streaming Generation
Work on efficient large-language-model inference has concentrated almost entirely on reducing the cost of decoding once a request is complete.The Scheduler Is a Hidden Retriever: How Asynchrony Shapes Evidence Acquisition in Search Agents
Language-model agents increasingly solve complex tasks through parallel reasoning and asynchronous information gathering.Typed Decision Models under Prevalence Shift: Decision Training, Calibration, and Implicit Priors
Typed decision models (TDMs) return a probability over caller-defined options, and Jev is described by its vendor as calibrated.