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Typological Feature Induction as a Benchmark for Inductive Metalinguistic Reasoning
Existing metalinguistic reasoning benchmarks require both inference of rules and their application, making failures hard to diagnose.Sketchpad: certified exact arithmetic with a small vision-language model
Language models are accurate on most long-arithmetic problems, but their accuracy is estimated on samples and carries no guarantee for an unseen input; tool use is exact but moves the computation…Near-Zero Token Embeddings Silently Stall Training in Gated Sequence Models
Among 291 surveyed open-weight language model repositories (280 distinct embedding tables), 52.6% of untied gated and hybrid checkpoints (20/38) contain reachable input embeddings with norms below…Large Language Model-Assisted Adaptive Heuristic Search for Agile Earth Observation Satellite Scheduling
Agile Earth observation satellites must coordinate imaging tasks within limited observation windows, while accounting for attitude maneuvering and onboard energy constraints.$τ$-Rec-Books: A Disclosure-Controlled Benchmark for Requirement Elicitation in Agentic Recommender Systems
While conversational recommendation systems provide a more natural user interface, they face the challenge of progressively discovering a user's needs before they can recommend an item that…ReListen: Training-Free Evidence Localization in Hour-Long Audio with Frozen Audio Language Models
Audio language models are meant to answer questions from the audio itself, but an hour-long recording rarely fits in their context, and the answer often depends on a few seconds of it.TEMPO: Time Series Understanding via Discrete Tokenization
Time-series interpretation often requires both numerical observations and textual context.Evaluating LLMs as Judges of Counterspeech Quality Against Online Hate Speech
Prolonged exposure to hate speech on social media can cause lasting psychological distress among users.Self-Privileged Fine-Tuning
Supervised fine-tuning (SFT) is a key component of language model post-training, enabling effective task adaptation and serving as an important foundation for subsequent reinforcement learning.MIMIC-Note-Extract: A Large-Scale Structured Dataset Extracted from MIMIC-IV-Note Discharge Summaries
MIMIC is one of the most widely used public hospital datasets for machine learning on electronic health records, yet clinically important information, such as past medical history, allergies, and…CardioVascBench:Prioritized Diagnosis Generation from Real-World Chinese Cardiovascular Records
Identifying the primary diagnosis alone does not fully characterize a model's diagnosis-generation performance.When Ground Truth Is Not Ground Truth: Automatic Labeling for Hallucination Detection
Hallucinations in Large Language Models (LLMs) remain a major challenge, as they can produce misleading, factually incorrect, or unverifiable information, thereby undermining their trustworthiness…ReSI-Math: Exploring Recoverable Capability Frontiers for Efficient Reasoning Improvement
Reinforcement learning with verifiable rewards (RLVR) has become an effective approach for improving mathematical reasoning in large language models.Where Is the Truth When AI Agents Disagree? Dependence-Aware Belief Propagation for Unsupervised Truth Discovery (Extended Version)
LLM agents often give conflicting answers to the same question, and many deployed agents are variants of one base model, so their errors are correlated.Think Less, Locally: Local Preference Learning for Reasoning Compression
Large reasoning models achieve strong performance on challenging tasks, but their long chain-of-thought often incurs substantial inference costs by continuing to deliberate after sufficient…Feeling of Knowing in Large Language Models
Post-training updates change what large language models (LLMs) can answer, but may leave their answerability judgments misaligned.One Assistant, Many Memories: Benchmarking Real-World Group Assistance When Recall Is Not Enough
The value of memory lies not only in recall but in using it to provide appropriate assistance.TraceRouter++: Causal Semantic Routing Realignment via Optimal Transport
Despite their remarkable capabilities, large foundation models (LFMs) remain susceptible to adversarial manipulation.Heads That Write, Not Just Point: Image Retrieval Heads in Vision-Language Models
Large vision-language models (LVLMs) can process interleaved text and multiple images in a single context, but how they internally identify the image relevant to a question remains poorly understood.PROSE: Preservation-Constrained Selective Editing for Guilty Bias in Legal Judgment Prediction
Legal judgment prediction models may retain a guilty verdict after a legally decisive condition has been altered such that the specified charge is no longer established.