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Newest papers, page 208
Fair Fact-Checking: Closing the Cross-Lingual Gap in LLM Factual Judgement with RoSh
Misinformation on social media remains a critical problem, and more and more people settle it by asking a language model instead of a fact checker.Using LLMs to Detect LLM-Generated Texts: A Cross-Generation Analysis
Automated detection of LLM-generated texts (LGTs) is critical, yet dedicated detectors often struggle to generalize across domains and models.ReMCTS: Reflection-Enhanced Monte Carlo Tree Search for Code Generation
Open-weight large language models (LLMs) can generate function-level programs from natural-language prompts, but plausible candidates still fail on hidden semantics and repeat mistakes across repair…Quality Determines Direction, Length Shapes Magnitude: Length Control for Open-Ended Reinforcement Learning
Reinforcement learning (RL) changes not only what language models say, but also how much they say, often increasing response length at the cost of token efficiency.SeLMRoute: Probabilistic Semantic Evidence for Large Language Model Routing
Large language model (LLM) routing aims to select the most suitable model for each incoming query.Beyond Token Alignment: Event Completion for Cross-Tokenizer On-Policy Distillation
On-policy distillation (OPD) transfers knowledge between language models through teacher supervision on student-generated trajectories.Draft-KV: Learning Useful Latent Communication Between Language Models
Latent communication passes internal states between language models instead of decoded text, but higher receiver accuracy does not show that the receiver used the message content.LongPuzzleBench: Evaluating GUI Agents on Long-Horizon Visual Puzzles
GUI agents need long-horizon visual reasoning: they must interpret a changing interface while keeping a multi-step plan viable as earlier actions constrain later ones.Reference-Grounded Data Curation for Instruction-Following Thai-English Machine Translation
Instruction-following machine translation (IF-MT) requires respecting prompt-level rules on terminology, formatting, and register.When Do Model Internals Help? Exploring the Role of Representation Engineering in LLM Safety
Reliable AI safeguards require both control mechanisms that reduce unsafe behavior and monitoring mechanisms that detect safety risks during model interactions.TQTS-Bench: A Multi-Syntax Benchmark for Text-to-Query over Time-Series Databases
Large language models (LLMs) have significantly advanced natural language querying over relational databases, yet their ability to query time-series databases (TSDBs) remains largely unassessed.InfiMed2: A Generalist Medical Multimodal Foundation Model from Contextual Evidence and Stability-Aware Supervision
Recent medical multimodal models have benefited from larger corpora, broader modality coverage, and stronger reasoning-oriented training, yet effective data design across continued pretraining (CPT)…Pass or Fail? Evaluating LLMs on Two Greek Examination Benchmarks
The rapid advancement of Large Language Models (LLMs) imposes a thorough evaluation of their linguistic and analytical capabilities as well as constraints, particularly for a language with limited…From Weak Task Specifications to Scientific Extraction Agents: Optimizing Task Construction
Most methods that optimize LLM prompts and agent workflows assume that task-specific output schemas, extraction instructions, and evaluation criteria are predefined.BV Loss: Block Verification-Aware Loss for Block Diffusion Speculative Decoding
Diffusion drafters accelerate speculative decoding by proposing multiple tokens in parallel.DivOPD: Spread Wide, Look Close for Asynchronous On-Policy Distillation of Multi-turn Agents
On-policy distillation (OPD) trains student agents through teacher supervision on their own interactions with an environment.OpenWhistle: A Large-Scale Longitudinal Dataset and Benchmark of Bottlenose Dolphin Vocalizations
Recent advances in bioacoustics have been driven by large-scale corpora and standardized benchmarks, yet existing resources are overwhelmingly bird-centric and shallow per species, limiting their…Adapt Semantics, Not Structure: Few-Instance Schema Calibration for Scientific PDF Extraction
A well-designed extraction schema is not necessarily ready for reliable LLM execution.Beyond Verbalized Confidence: Calibrating Reasoners with Differentiable Readouts
Reinforcement learning with verifiable rewards (RLVR) trains reasoning models to produce correct answers, but does not ensure that their stated confidence is calibrated.One Readout, Many Repairs: Diffusion-Guided Hierarchical Search for Tool-Agent Repair
Tool agents use large language models to act through external tools, yet successfully executed calls can still leave user requests unfulfilled.