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Newest papers, page 103
Training Reasoning Models to Generate Diverse Scientific Ideas
One of the first steps of a research pipeline is generating ideas.Twice Upon a Time: Complementary Representations for Time-Series Reasoning
Time Series Language Models (TSLMs) enable language-based understanding and reasoning over temporal data, yet a fundamental question remains: what information should their time-series…Evaluation Awareness Beyond English: Do LLMs Act Differently When Tested in Indic Languages?
Large language models (LLMs) can often tell when they are being tested.MLExpert: Towards a Generalist Agentic Model for Autonomous Machine Learning Engineering
Large language models (LLMs) are expanding from assisting scientific research and engineering to autonomously developing and improving AI systems, advancing AI for AI (AI4AI) as a pathway toward…FDE-Gym: The Last Mile of AI Delivery
Existing agent benchmarks typically evaluate agents on well-specified tasks defined by issue reports, specifications, or task tickets.OmniVerifier-C1: Decomposed Graded Verifier for Rule-Governed Generative World Modeling
Generative visual verifiers play a crucial role in advancing multimodal intelligence.PRIME: Towards Verifiable Evidence-Grounded Reasoning in LLM Agents
LLM agents are used to check records against an organization's requirements, for example whether a vulnerability report is ready for investigation.Embeddings Are Overpriced? A Frozen 16 MB Vocabulary for Small and Ternary Language Models
In a small language model the vocabulary is the single largest part.Where Prefill Expert Reduction Hurts MoE Models: A Few Prompt Tokens Carry Most of the Short-Answer F1 Loss
Running prompt tokens through fewer routed experts during prefill is a simple way to make mixture-of-experts (MoE) serving cheaper, yet it is unclear what this damages.High prevalence of antagonizing rhetoric in trending topics on Twitter/X
Disagreement between political opponents is a central element of democracy.Progressive Misalignment Can Emerge from Benign Recursive Self-Distillation
Training models on their own outputs has attracted widespread attention as a possible route to advance AI capabilities.From Parallels to Divergence: Language Models' Learning of Action Nominal Constructions
Action nominal constructions (ANCs) express events in nominal form, with their argument marking following patterns found in clauses or ordinary noun phrases.RealCLI: Toward a Unified Evaluation of Human-Agent Collaboration for CLI Agents
Command-line interface (CLI) agents increasingly execute longer-horizon tasks, yet existing benchmarks either assume that user instructions remain fixed throughout execution or evaluate task…AuditKIT: A Unified Evaluation Spine for Benchmarking, Judging, and Comparing Large Language Models and Agentic Systems
Evaluating language models and agents requires combining benchmark accuracy, judge-based assessment, runtime performance, tool-use behavior, and retrieval quality.alkhder at ImageEval 2026 Shared Tasks: Constrained Selection and Rotation-Averaged Logit Scoring for Multimodal Hallucination Detection
We describe our submission to Subtask~1b of ImageEval 2026.Learning User Representations to Improve Simulation Fidelity
User simulators enable interactive training and evaluation of AI assistants at scale.alkhder at AlexandriaX-2026: Context-Aware English-to-Dialectal Arabic Dialogue Translation with QLoRA-Fine-Tuned NileChat-3B
This paper describes team Alkhder's submission to Subtask 1 of the AlexandriaX-2026 shared task, which asks systems to translate English dialogue turns into thirteen Arabic dialects.Literal Lock-In: How Test Language Shifts Literal Attraction in Typed Decision Models on Bengali Idioms
Decision models, non-generative scorers that report a probability over caller-supplied options and emit no text, are increasingly deployed as routers, classifiers and guardrails.Pearl-Chat: Engineering a native Luganda language model from first principles in JAX and Flax NNX
Autoregressive foundation language models predominantly target high-resource Indo-European languages, imposing computational and morphological penalties on under-represented African languages.Are Large Reasoning Models Good Everyday Reasoners? A Comparison with Non-Reasoning Models on Logical Reasoning Tasks
Large reasoning models (LRMs) that leverage test-time computation achieve strong performance on mathematical and scientific benchmarks and are increasingly deployed in real-world applications.