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Newest papers, page 135
KV-Repurpose: A Testbed for Evaluating Non-Prefix KV-Cache Reuse
KV-cache reuse in large language model serving is commonly limited to exact prompt prefixes, preventing reuse when the same retrieved document appears after different system prompts, conversation…From 2.1M Hours of Raw Broadcast Audio to Finnish Speech SSL: Confidence Filtering and Architectural Analysis at Scale
Broadcast archives offer scale and diversity for self-supervised learning (SSL) but contain substantial noisy, non-speech, and multilingual content.BenCoDiC: A Large-Scale Contextual Cyberbullying Corpus for Bengali Political News Discourse FULL VERSION
Cyberbullying is a growing concern in online communities, yet existing Bengali corpora remain limited in contextual information, annotation transparency, scale, accessibility, and support for…Locate, Judge, Read: Role-Specialized Tool Agents over a Knowledge-Point Index for Open-Domain Multimodal Document QA
Question answering over large heterogeneous document collections requires first finding the right passages and then reading them, yet current retrieval-augmented agents give one model both kinds of…Neurograf v1: An End-to-End Romanian-First Language Model Family
We present Neurograf v1, an experimental end-to-end Romanian-first language-model pipeline developed to investigate the feasibility of training language models from scratch for a lower-resource…Les Misérables Dialogue: A film-based network representation of social communication
In this work, we revisit the classic Les Misérables benchmark network from the perspective of social communication.SOAR: Source-Aware Reinforcement Learning with Precise Credit Assignment for Search Agents
Reinforcement learning (RL) for search agents often suffers from evidence fabrication, a failure mode where agents bypass external information ($E_{ext}$) and fabricate an incorrect answer.Scaling Agentic Data for Long-Horizon Terminal Intelligence
Terminal agents are moving beyond local operations toward completing real-world professional tasks.PreSTO: Predictive Subtree Prefetching for Fast LLM Power Sampling
Power sampling improves large language model (LLM) reasoning at test time by sampling from a sharpened version of the base model's distribution.JANUS: Enhancing Long-Horizon Autonomous Research with Co-Evolving World Models
Long-horizon autonomous research has shown promise in accelerating scientific progress through sustained cycles of hypothesis generation, implementation, and validation.S$^3$R: Fast and Faithful RL Rollouts via Self-Sparse Speculative Decoding
Fast rollout generation for long-context reinforcement learning with verifiable rewards (RLVR) requires reducing KV-cache traffic without changing the response groups used for policy optimization.SharP: Soft and Hard Prompt-Guided Augmentation with LLM for Low Resource Fake News Detection
Fake news detection under low resource conditions is challenged by the scarcity of labeled data and the difficulty of capturing subtle deceptive patterns.How Reliable are AMR Parser Outputs? Uncertainty Estimation for AMR Parsing
Recent advances have significantly improved the performance of Abstract Meaning Representation (AMR) parsers, yet determining when their outputs can be trusted remains largely unexplored.What Do Audio-Language Judges of Generated Music Listen For? Four Probes with Controls from Expert Ratings
Open audio-language models are used as judges of generated music: given a clip and its text prompt, the model rates the clip, and the judge is validated by how well its ratings correlate with expert…Vision Transformers Learn Word Meaning from Images Alone
Can a vision model learn what words mean from pixels alone?CAST: Credit Alignment for Cross-Tokenizer On-Policy Distillation
Cross-tokenizer on-policy distillation (OPD) requires aligning teacher and student sequences before their scores can be compared.Beyond the Final Embedding: Retrieving Memories from Token-Level Evidence
Memory-augmented assistants retrieve evidence from stored conversations and documents to answer queries.BoundaryEvo: Data-Model Co-Evolution at the Capability Boundary for Long-Chain Reasoning Distillation
Distilling long-chain reasoning trajectories from large teacher models provides an effective way to improve the reasoning ability of small language models.Do Prompt Optimizers Break Requirements They Are Not Scored On? A Preregistered Study
Prompt optimizers rewrite a prompt to raise one target metric, but prompts also state requirements the metric does not score, such as an output format, citations, or abstention.Agreement Without Alignment: Label-Free Rubric Clarification Increases LLM-Judge Consensus but Not Agreement with Humans
LLM judges are increasingly deployed as panels, and disagreement among panel members is often read as a symptom of an unclear rubric.